user-story-10-grant-outputs/py-grant-outputs-with-output.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ![FREYA Logo](https://github.com/datacite/pidgraph-notebooks-python/blob/master/images/freya_200x121.png?raw=true) | [FREYA](https://www.project-freya.eu/en) WP2 [User Story 10](https://github.com/datacite/freya/issues/45) | As a funder, we want to be able to find all the outputs related to our awarded grants, including block grants such as doctoral training grants, for management info and looking at impact. \n",
    " :------------- | :------------- | :-------------\n",
    "\n",
    "Funders are interested in monitoring the output of grants they award - while the grant is active as well as retrospectively. The quality, quantity and types of the grant's outputs are useful proxies for the value obtained as a result of the funder's investment.<p />\n",
    "This notebook uses the [DataCite GraphQL API](https://api.datacite.org/graphql) to retrieve all outputs of [FREYA grant award](https://cordis.europa.eu/project/id/777523) from [European Union](https://doi.org/10.13039/501100000780) to date. \n",
    "\n",
    "**Goal**: By the end of this notebook you should be able to:\n",
    "- Retrieve all outputs of a grant award from a specific funder; \n",
    "- Plot number of outputs per year-quarter of the grant award duration;\n",
    "- Display de-duplicated outputs in tabular format, including the number of their citations, views and downloads;\n",
    "- Plot a pie chart of the number of outputs per resource type;\n",
    "- Display an interactive chord plot of co-authorship relationships across all outputs, e.g. <br> <img src=\"example_plot.png\" width=\"318\" height=\"309\" />\n",
    "- Plot a pie chart of the number of outputs per license type;\n",
    "- Plot an interactive stacked bar plot showing the proportion of outputs of each type issued under a given license type."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Install libraries and prepare GraphQL client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "# Install required Python packages\n",
    "!pip install gql requests chord==0.0.17 numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare the GraphQL client\n",
    "import requests\n",
    "from IPython.display import display, Markdown\n",
    "from gql import gql, Client\n",
    "from gql.transport.requests import RequestsHTTPTransport\n",
    "\n",
    "_transport = RequestsHTTPTransport(\n",
    "    url='https://api.datacite.org/graphql',\n",
    "    use_json=True,\n",
    ")\n",
    "\n",
    "client = Client(\n",
    "    transport=_transport,\n",
    "    fetch_schema_from_transport=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define and run GraphQL query\n",
    "Define the GraphQL query to find all outputs of [FREYA grant award](https://cordis.europa.eu/project/id/777523) from [European Union](https://doi.org/10.13039/501100000780) to date."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate the GraphQL query: find all outputs of FREYA grant award (https://cordis.europa.eu/project/id/777523) from funder (EU) to date\n",
    "query_params = {\n",
    "    \"funderId\" : \"https://doi.org/10.13039/501100000780\",\n",
    "    \"funderAwardQuery\" : \"fundingReferences.awardNumber:777523\",\n",
    "    \"maxWorks\" : 200\n",
    "}\n",
    "\n",
    "query = gql(\"\"\"query getGrantOutputsForFunderAndAward($funderId: ID!, $funderAwardQuery: String!, $maxWorks: Int!)\n",
    "{\n",
    "funder(id: $funderId) {\n",
    "  name\n",
    "  works(query: $funderAwardQuery, first: $maxWorks) {\n",
    "      totalCount\n",
    "      nodes {\n",
    "        id\n",
    "        formattedCitation(style: \"vancouver\")\n",
    "        titles {\n",
    "          title\n",
    "        }\n",
    "        descriptions {\n",
    "          description\n",
    "        }        \n",
    "        types {\n",
    "          resourceType\n",
    "        }\n",
    "        dates {\n",
    "          date\n",
    "          dateType\n",
    "        }\n",
    "        versionOfCount\n",
    "        rights {\n",
    "          rights\n",
    "          rightsIdentifier\n",
    "          rightsUri\n",
    "        }        \n",
    "        creators {\n",
    "          id\n",
    "          name\n",
    "        }\n",
    "        fundingReferences {\n",
    "          funderIdentifier\n",
    "          funderName\n",
    "          awardNumber\n",
    "          awardTitle\n",
    "        }\n",
    "        citationCount\n",
    "        viewCount\n",
    "        downloadCount\n",
    "      }\n",
    "    }\n",
    "  }\n",
    "}\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the above query via the GraphQL client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "data = client.execute(query, variable_values=json.dumps(query_params))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display total number of works \n",
    "Display the total number of [FREYA grant award](https://cordis.europa.eu/project/id/777523) outputs to date."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "92"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get the total number of outputs to date\n",
    "funder = data['funder']['works']\n",
    "display(Markdown(str(funder['totalCount'])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot number of works per quarter\n",
    "Display a bar plot of number of [FREYA grant award](https://cordis.europa.eu/project/id/777523) outputs to date, per each quarter of project's duration."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11aa0fe10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the number of FREYA outputs to date, by year\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import FormatStrFormatter\n",
    "import numpy as np\n",
    "\n",
    "# Return quarter (number) given month (number)\n",
    "def get_quarter(month):\n",
    "    return (month - 1) // 3 + 1\n",
    "\n",
    "# Return list of consecutive years between min_year_quarter and max_year_quarter inclusive\n",
    "def get_consecutive_year_quarters(min_year_quarter, max_year_quarter):\n",
    "    year_quarters = [\"%d Q%d\" % (min_year_quarter[0],min_year_quarter[1])]\n",
    "    yq = min_year_quarter\n",
    "    while yq != max_year_quarter:\n",
    "        year = yq[0]\n",
    "        quarter = yq[1]\n",
    "        if quarter == 4:\n",
    "            year += 1\n",
    "            quarter = 1\n",
    "        else:\n",
    "            quarter += 1\n",
    "        yq = (year, quarter)\n",
    "        year_quarters.append(\"%d Q%d\" % (year,quarter))\n",
    "    year_quarters.append(\"%d Q%d\" % (max_year_quarter[0],max_year_quarter[1])) \n",
    "    return year_quarters\n",
    "\n",
    "plt.rcdefaults()\n",
    "\n",
    "# Retrieve works counts by year-quarter from nodes\n",
    "# Pick out date of type: 'Issued'; failing that use 'Created' date.\n",
    "num_outputs_dict = {}\n",
    "funder = data['funder']['works']\n",
    "for r in funder['nodes']:\n",
    "    node_date = None\n",
    "    for date_dict in r['dates']:\n",
    "        ym = date_dict['date'].split('-')[0:2]\n",
    "        if len(ym) < 2:\n",
    "            continue\n",
    "        yq = ym[0] + \" Q\" + str(get_quarter(int(ym[1])))\n",
    "        if node_date is None:\n",
    "            if date_dict['dateType'] in ['Issued', 'Created']:\n",
    "                node_date = yq\n",
    "        else:\n",
    "            if date_dict['dateType'] in ['Issued']:\n",
    "                node_date = yq\n",
    "    if node_date:\n",
    "        if node_date not in num_outputs_dict:\n",
    "            num_outputs_dict[node_date] = 0\n",
    "        num_outputs_dict[node_date] += 1;\n",
    "    \n",
    "# Sort works counts by year-quarter in chronological order\n",
    "sorted_year_quarters = sorted(list(num_outputs_dict.keys()))\n",
    "# Get all consecutive year-quarters FREYA-specific start-end year-quarter\n",
    "year_quarters = get_consecutive_year_quarters((2017,4), (2020,4))       \n",
    "# Populate non-zero counts for year_quarters                          \n",
    "num_outputs = []\n",
    "for yq in year_quarters:\n",
    "    if yq in sorted_year_quarters:\n",
    "        num_outputs.append(num_outputs_dict[yq])\n",
    "    else:\n",
    "        num_outputs.append(0)\n",
    "        \n",
    "# Generate a plot of number of grant outputs by year - quarter\n",
    "fig, ax = plt.subplots(1, 1, figsize = (10, 5))\n",
    "x_pos = np.arange(len(year_quarters))\n",
    "ax.bar(x_pos, num_outputs, align='center', color='blue', edgecolor='black', linewidth = 0.1, alpha=0.5)\n",
    "ax.set_xticks(x_pos)\n",
    "ax.set_xticklabels(year_quarters, rotation='vertical')\n",
    "ax.set_ylabel('Number of outputs')\n",
    "ax.set_xlabel('Year Quarter')\n",
    "ax.set_title('Number of Grant Award Outputs per Year-Quarter')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display de-duplicated works in tabular format\n",
    "Display the outputs of [FREYA grant award](https://cordis.europa.eu/project/id/777523) in a html table, including the number of their citations, views and downloads. Note that the outputs are de-duplicated, i.e. outputs that are versions of another output are excluded."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<html><table><tr><th style=\"text-align:center;\">ID</th><th style=\"text-align:center;\">Type</th><th style=\"text-align:center;\">Publication Date</th><th style=\"text-align:center;\">Formatted Citation</th><th style=\"text-align:center;\">Descriptions</th><th style=\"text-align:center;\">Number of Citations</th><th style=\"text-align:center;\">Number of Views</th><th style=\"text-align:center;\">Number of Downloads</th></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.1202173\">10.5281/zenodo.1202173</a></html></td><td style=\"text-align:left;\">General</td><td style=\"text-align:left;\">2018-03-17</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0003-1304-1939\">Crosas, Merce</a>; <a href=\"https://orcid.org/0000-0002-2188-2570\">Durand, Gustavo</a>; <a href=\"https://orcid.org/0000-0002-5355-2576\">Wimalaratne, Sarala</a>; <a href=\"https://orcid.org/0000-0003-4890-5979\">Gräf, Florian</a>; <a href=\"https://orcid.org/0000-0002-8599-0773\">Hallett, Richard</a>; <a href=\"https://orcid.org/0000-0002-7368-180X\">Bernal Llinares, Manuel</a>; <a href=\"https://orcid.org/0000-0002-1900-4162\">Schindler, Uwe</a>; <a href=\"https://orcid.org/0000-0003-4060-7360\">Clark, Tim</a>. Listing of data repositories that embed schema.org metadata in dataset landing pages. 2018-03-17; Available from: <a href=\"https://doi.org/10.5281/zenodo.1202173\">10.5281/zenodo.1202173</a></html></td><td style=\"text-align:left;\">Machine-readable metadata available from landing pages for datasets facilitate data citation by enabling easy integration with reference managers and other tools used in a data citation workflow....</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.1263942\">10.5281/zenodo.1263942</a></html></td><td style=\"text-align:left;\">General</td><td style=\"text-align:left;\">2018-03-17</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0003-1304-1939\">Crosas, Merce</a>; <a href=\"https://orcid.org/0000-0002-2188-2570\">Durand, Gustavo</a>; <a href=\"https://orcid.org/0000-0002-5355-2576\">Wimalaratne, Sarala</a>; <a href=\"https://orcid.org/0000-0003-4890-5979\">Gräf, Florian</a>; <a href=\"https://orcid.org/0000-0002-8599-0773\">Hallett, Richard</a>; <a href=\"https://orcid.org/0000-0002-7368-180X\">Bernal Llinares, Manuel</a>; <a href=\"https://orcid.org/0000-0002-1900-4162\">Schindler, Uwe</a>; <a href=\"https://orcid.org/0000-0003-4060-7360\">Clark, Tim</a>. Listing of data repositories that embed schema.org metadata in dataset landing pages. 2018-03-17; Available from: <a href=\"https://doi.org/10.5281/zenodo.1263942\">10.5281/zenodo.1263942</a></html></td><td style=\"text-align:left;\">Machine-readable metadata available from landing pages for datasets facilitate data citation by enabling easy integration with reference managers and other tools used in a data citation workflow....</td><td style=\"text-align:left;\">2</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.2548715\">10.5281/zenodo.2548715</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-01-24</td><td style=\"text-align:left;\"><a href=\"None\">Simons, Natasha</a>; <a href=\"None\">Brown, Christopher</a>; <a href=\"https://orcid.org/0000-0001-6383-7148\">Braukmann, Ricarda</a>. Adventure Time: the PID community challenge - Presentation at PIDapalooza19. 2019-01-24; Available from: <a href=\"https://doi.org/10.5281/zenodo.2548715\">10.5281/zenodo.2548715</a></html></td><td style=\"text-align:left;\">Presentation of the \"Adventure Time: the PID community challenge\" - session at PIDapalooza19. Abstract of the session: PIDs are a core component of open research across the global scholarly...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.2548714\">10.5281/zenodo.2548714</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-01-24</td><td style=\"text-align:left;\"><a href=\"None\">Simons, Natasha</a>; <a href=\"None\">Brown, Christopher</a>; <a href=\"https://orcid.org/0000-0001-6383-7148\">Braukmann, Ricarda</a>. Adventure Time: the PID community challenge - Presentation at PIDapalooza19. 2019-01-24; Available from: <a href=\"https://doi.org/10.5281/zenodo.2548714\">10.5281/zenodo.2548714</a></html></td><td style=\"text-align:left;\">Presentation of the \"Adventure Time: the PID community challenge\" - session at PIDapalooza19. Abstract of the session: PIDs are a core component of open research across the global scholarly...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.2549227\">10.5281/zenodo.2549227</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-01-25</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-8357-9422\">Reimer, Torsten</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. From Standard to Community Resource: A View on ISNIs and ORG IDs. 2019-01-25; Available from: <a href=\"https://doi.org/10.5281/zenodo.2549227\">10.5281/zenodo.2549227</a></html></td><td style=\"text-align:left;\">Over the last year, the International Standard Name Identifier board have been considering the ways in which ISNI as a system can improve to meet new challenges and become more open and...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.2552138\">10.5281/zenodo.2552138</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-01-29</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5228-1970\">Baars, Chris</a>; <a href=\"https://orcid.org/0000-0003-4803-7411\">De Jong, Maaike</a>. NARCIS &amp; FREYA Can PIDs contribute to research in context?. 2019-01-29; Available from: <a href=\"https://doi.org/10.5281/zenodo.2552138\">10.5281/zenodo.2552138</a></html></td><td style=\"text-align:left;\"><em>Abstract:</em> NARCIS, the national gateway to scholarly information in the Netherlands (www.narcis.nl) contains information about publications, datasets, research projects, researchers and...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.2552137\">10.5281/zenodo.2552137</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-01-29</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5228-1970\">Baars, Chris</a>; <a href=\"https://orcid.org/0000-0003-4803-7411\">De Jong, Maaike</a>. NARCIS &amp; FREYA Can PIDs contribute to research in context?. 2019-01-29; Available from: <a href=\"https://doi.org/10.5281/zenodo.2552137\">10.5281/zenodo.2552137</a></html></td><td style=\"text-align:left;\"><em>Abstract:</em> NARCIS, the national gateway to scholarly information in the Netherlands (www.narcis.nl) contains information about publications, datasets, research projects, researchers and...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5438/jwvf-8a66\">10.5438/jwvf-8a66</a></html></td><td style=\"text-align:left;\">BlogPosting</td><td style=\"text-align:left;\">2019</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0002-4259-9774\">Aryani, Amir</a>. Introducing the PID Graph. 2019; Available from: <a href=\"https://doi.org/10.5438/jwvf-8a66\">10.5438/jwvf-8a66</a></html></td><td style=\"text-align:left;\"><em>This post has been cross-posted from the FREYA blog.</em> Persistent identifiers (PIDs) are not only important to uniquely identify a publication, dataset, or person, but the metadata for these...</td><td style=\"text-align:left;\">4</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5438/wy92-xj57\">10.5438/wy92-xj57</a></html></td><td style=\"text-align:left;\">BlogPosting</td><td style=\"text-align:left;\">2019-04-10</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. Exposing DOI metadata provenance. 2019-04-10; Available from: <a href=\"https://doi.org/10.5438/wy92-xj57\">10.5438/wy92-xj57</a></html></td><td style=\"text-align:left;\">DOI metadata provenance is describing the history of a particular DOI metadata record, i.e. what changes were made when and by whom. This information is now stored and provided via an API for all...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.2649230\">10.5281/zenodo.2649230</a></html></td><td style=\"text-align:left;\">Report</td><td style=\"text-align:left;\">2019-04-23</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>; <a href=\"https://orcid.org/0000-0002-1611-6935\">McEntyre, Johanna</a>; <a href=\"https://orcid.org/0000-0002-0353-2702\">Hendricks, Ginny</a>; <a href=\"https://orcid.org/0000-0002-5948-0980\">Dohna, Tina</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jakobsen, Ketil</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0002-6137-2348\">Dallmeier-Tiessen, Sunje</a>; <a href=\"https://orcid.org/0000-0002-9576-1974\">Sandt, Stephanie Van De</a>; <a href=\"https://orcid.org/0000-0001-5633-2459\">Lavasa, Artemis</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0003-3467-5690\">Bunakov, Vasily</a>; <a href=\"https://orcid.org/0000-0002-4695-7874\">Dasler, Robin</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. Deliverable D3.2 Requirements for Selected New PID Services. 2019-04-23; Available from: <a href=\"https://doi.org/10.5281/zenodo.2649230\">10.5281/zenodo.2649230</a></html></td><td style=\"text-align:left;\">A comprehensive analysis of user stories relating to a range of entities needing persistent identifiers, with conclusions for further work in the FREYA project.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.2649229\">10.5281/zenodo.2649229</a></html></td><td style=\"text-align:left;\">Report</td><td style=\"text-align:left;\">2019-04-28</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>; <a href=\"https://orcid.org/0000-0002-1611-6935\">McEntyre, Johanna</a>; <a href=\"https://orcid.org/0000-0002-0353-2702\">Hendricks, Ginny</a>; <a href=\"https://orcid.org/0000-0002-5948-0980\">Dohna, Tina</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jakobsen, Ketil</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0002-6137-2348\">Dallmeier-Tiessen, Sunje</a>; <a href=\"https://orcid.org/0000-0002-9576-1974\">Sandt, Stephanie Van De</a>; <a href=\"https://orcid.org/0000-0001-5633-2459\">Lavasa, Artemis</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0003-3467-5690\">Bunakov, Vasily</a>; <a href=\"https://orcid.org/0000-0002-4695-7874\">Dasler, Robin</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. Deliverable D3.2 Requirements for Selected New PID Services. 2019-04-28; Available from: <a href=\"https://doi.org/10.5281/zenodo.2649229\">10.5281/zenodo.2649229</a></html></td><td style=\"text-align:left;\">A comprehensive analysis of user stories relating to a range of entities needing persistent identifiers, with conclusions for further work in the FREYA project. The deliverable was updated after...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5438/qab1-n315\">10.5438/qab1-n315</a></html></td><td style=\"text-align:left;\">BlogPosting</td><td style=\"text-align:left;\">2019</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. The DataCite GraphQL API is now open for (pre-release) business. 2019; Available from: <a href=\"https://doi.org/10.5438/qab1-n315\">10.5438/qab1-n315</a></html></td><td style=\"text-align:left;\">DataCite DOIs describe resources such as datasets, samples, software and publications with rich metadata. An important part of this metadata is the description of connections between resources that...</td><td style=\"text-align:left;\">3</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.2866420\">10.5281/zenodo.2866420</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-05-14</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-8876-7606\">Chue Hong, Neil</a>; <a href=\"https://orcid.org/0000-0003-3629-1383\">Cope, Jez</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. Setting the Scene to Cite Software. 2019-05-14; Available from: <a href=\"https://doi.org/10.5281/zenodo.2866420\">10.5281/zenodo.2866420</a></html></td><td style=\"text-align:left;\">Introduction to Day 2 of the Software Citation Workshop organised by the Software Sustainability Institute, the British Library and The Alan Turing Institute.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.2866419\">10.5281/zenodo.2866419</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-05-14</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-8876-7606\">Chue Hong, Neil</a>; <a href=\"https://orcid.org/0000-0003-3629-1383\">Cope, Jez</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. Setting the Scene to Cite Software. 2019-05-14; Available from: <a href=\"https://doi.org/10.5281/zenodo.2866419\">10.5281/zenodo.2866419</a></html></td><td style=\"text-align:left;\">Introduction to Day 2 of the Software Citation Workshop organised by the Software Sustainability Institute, the British Library and The Alan Turing Institute.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5438/hwaw-xe52\">10.5438/hwaw-xe52</a></html></td><td style=\"text-align:left;\">BlogPosting</td><td style=\"text-align:left;\">2019</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. Using Jupyter Notebooks with GraphQL and the PID Graph. 2019; Available from: <a href=\"https://doi.org/10.5438/hwaw-xe52\">10.5438/hwaw-xe52</a></html></td><td style=\"text-align:left;\">Two weeks ago DataCite announced the pre-release version of a GraphQL API [Fenner (2019)]. GraphQL simplifies complex queries that for example want to retrieve information about the authors,...</td><td style=\"text-align:left;\">2</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3248653\">10.5281/zenodo.3248653</a></html></td><td style=\"text-align:left;\">Project deliverable</td><td style=\"text-align:left;\">2019-06-18</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0002-0840-454X\">Wass, Joe</a>; <a href=\"https://orcid.org/0000-0003-0902-4386\">Demeranville, Tom</a>; <a href=\"https://orcid.org/0000-0002-5355-2576\">Wimalaratne, Sarala</a>; <a href=\"https://orcid.org/0000-0002-8599-0773\">Hallett, Richard</a>. D2.2 PID Metadata Provenance. 2019-06-18; Available from: <a href=\"https://doi.org/10.5281/zenodo.3248653\">10.5281/zenodo.3248653</a></html></td><td style=\"text-align:left;\">The main focus of this document is describing the implementations of provenance tracking by the persistent identifier (PID) providers Crossref, ORCID, Identifiers.org (EMBL-EBI), and DataCite in...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3248652\">10.5281/zenodo.3248652</a></html></td><td style=\"text-align:left;\">Project deliverable</td><td style=\"text-align:left;\">2019-06-18</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0002-0840-454X\">Wass, Joe</a>; <a href=\"https://orcid.org/0000-0003-0902-4386\">Demeranville, Tom</a>; <a href=\"https://orcid.org/0000-0002-5355-2576\">Wimalaratne, Sarala</a>; <a href=\"https://orcid.org/0000-0002-8599-0773\">Hallett, Richard</a>. D2.2 PID Metadata Provenance. 2019-06-18; Available from: <a href=\"https://doi.org/10.5281/zenodo.3248652\">10.5281/zenodo.3248652</a></html></td><td style=\"text-align:left;\">The main focus of this document is describing the implementations of provenance tracking by the persistent identifier (PID) providers Crossref, ORCID, Identifiers.org (EMBL-EBI), and DataCite in...</td><td style=\"text-align:left;\">1</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3249833\">10.5281/zenodo.3249833</a></html></td><td style=\"text-align:left;\">Project deliverable</td><td style=\"text-align:left;\">2019-06-19</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-5633-2459\">Lavasa, Artemis</a>; <a href=\"https://orcid.org/0000-0002-6137-2348\">Dallmeier-Tiessen, Sünje</a>; <a href=\"https://orcid.org/0000-0002-9576-1974\">Sandt, Stephanie Van De</a>; <a href=\"https://orcid.org/0000-0002-5948-0980\">Dohna, Tina</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jakobsen, Ketil</a>; <a href=\"https://orcid.org/0000-0002-1900-4162\">Schindler, Uwe</a>; <a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>; <a href=\"https://orcid.org/0000-0002-1611-6935\">McEntyre, Johanna</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0003-3467-5690\">Bunakov, Vasily</a>; <a href=\"https://orcid.org/0000-0002-5228-1970\">Baars, Chris</a>. D4.2 Using the PID Graph: Provenance in Disciplinary Systems. 2019-06-19; Available from: <a href=\"https://doi.org/10.5281/zenodo.3249833\">10.5281/zenodo.3249833</a></html></td><td style=\"text-align:left;\">The main focus of this deliverable is the different approaches to provenance as understood, expressed, and implemented by the FREYA disciplinary partners in their various pilot applications. The...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3249832\">10.5281/zenodo.3249832</a></html></td><td style=\"text-align:left;\">Project deliverable</td><td style=\"text-align:left;\">2019-06-19</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-5633-2459\">Lavasa, Artemis</a>; <a href=\"https://orcid.org/0000-0002-6137-2348\">Dallmeier-Tiessen, Sünje</a>; <a href=\"https://orcid.org/0000-0002-9576-1974\">Sandt, Stephanie Van De</a>; <a href=\"https://orcid.org/0000-0002-5948-0980\">Dohna, Tina</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jakobsen, Ketil</a>; <a href=\"https://orcid.org/0000-0002-1900-4162\">Schindler, Uwe</a>; <a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>; <a href=\"https://orcid.org/0000-0002-1611-6935\">McEntyre, Johanna</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0003-3467-5690\">Bunakov, Vasily</a>; <a href=\"https://orcid.org/0000-0002-5228-1970\">Baars, Chris</a>. D4.2 Using the PID Graph: Provenance in Disciplinary Systems. 2019-06-19; Available from: <a href=\"https://doi.org/10.5281/zenodo.3249832\">10.5281/zenodo.3249832</a></html></td><td style=\"text-align:left;\">The main focus of this deliverable is the different approaches to provenance as understood, expressed, and implemented by the FREYA disciplinary partners in their various pilot applications. The...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3250702\">10.5281/zenodo.3250702</a></html></td><td style=\"text-align:left;\">Project deliverable</td><td style=\"text-align:left;\">2019-06-20</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>. D6.1 First Annual Report on PID Commons and Sustainability. 2019-06-20; Available from: <a href=\"https://doi.org/10.5281/zenodo.3250702\">10.5281/zenodo.3250702</a></html></td><td style=\"text-align:left;\">The first report on FREYA’s sustainability takes a wide view of the meaning and requirements on sustainability that the context of the project imply. The “what”, “who” and “how” of sustainability...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3250701\">10.5281/zenodo.3250701</a></html></td><td style=\"text-align:left;\">Project deliverable</td><td style=\"text-align:left;\">2019-06-20</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>. D6.1 First Annual Report on PID Commons and Sustainability. 2019-06-20; Available from: <a href=\"https://doi.org/10.5281/zenodo.3250701\">10.5281/zenodo.3250701</a></html></td><td style=\"text-align:left;\">The first report on FREYA’s sustainability takes a wide view of the meaning and requirements on sustainability that the context of the project imply. The “what”, “who” and “how” of sustainability...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.14454/3bpw-w381\">10.14454/3bpw-w381</a></html></td><td style=\"text-align:left;\">Computational Notebook</td><td style=\"text-align:left;\">2019-06-30</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. Jupyter Notebook FREYA PID Graph Key Performance Indicators (KPIs). 2019-06-30; Available from: <a href=\"https://doi.org/10.14454/3bpw-w381\">10.14454/3bpw-w381</a></html></td><td style=\"text-align:left;\"></td><td style=\"text-align:left;\">2</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5438/bv9z-dc66\">10.5438/bv9z-dc66</a></html></td><td style=\"text-align:left;\">BlogPosting</td><td style=\"text-align:left;\">2019-07-01</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. Tracking the Growth of the PID Graph. 2019-07-01; Available from: <a href=\"https://doi.org/10.5438/bv9z-dc66\">10.5438/bv9z-dc66</a></html></td><td style=\"text-align:left;\">The connections between scholarly resources generated by persistent identifiers (PIDs) and associated metadata form a graph: the PID Graph [Fenner &amp; Aryani (2019)]. We developed this PID Graph...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361391\">10.5281/zenodo.3361391</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. FREYA RDA UK Workshop July 2019. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361391\">10.5281/zenodo.3361391</a></html></td><td style=\"text-align:left;\">Presentation introducing the FREYA project at a joint RDA UK and FREYA workshop held 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361390\">10.5281/zenodo.3361390</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. FREYA RDA UK Workshop July 2019. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361390\">10.5281/zenodo.3361390</a></html></td><td style=\"text-align:left;\">Presentation introducing the FREYA project at a joint RDA UK and FREYA workshop held 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361397\">10.5281/zenodo.3361397</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-06-26</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. The Power of PIDs. 2019-06-26; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361397\">10.5281/zenodo.3361397</a></html></td><td style=\"text-align:left;\">Lightning Talk slide presented at Carpentry Connect 2019 in Manchester UK.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361396\">10.5281/zenodo.3361396</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-06-26</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. The Power of PIDs. 2019-06-26; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361396\">10.5281/zenodo.3361396</a></html></td><td style=\"text-align:left;\">Lightning Talk slide presented at Carpentry Connect 2019 in Manchester UK.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361429\">10.5281/zenodo.3361429</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-5800-1434\">Lammey, Rachael</a>. Embracing funder workflows (or Grant why-ds…). 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361429\">10.5281/zenodo.3361429</a></html></td><td style=\"text-align:left;\">Presentation on how Crossref are starting to implement persistent identifiers for grants. Presented at RDA UK FREYA workshop,16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361430\">10.5281/zenodo.3361430</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-5800-1434\">Lammey, Rachael</a>. Embracing funder workflows (or Grant why-ds…). 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361430\">10.5281/zenodo.3361430</a></html></td><td style=\"text-align:left;\">Presentation on how Crossref are starting to implement persistent identifiers for grants. Presented at RDA UK FREYA workshop,16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361436\">10.5281/zenodo.3361436</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>. Preprints and literature provenance in Europe PMC. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361436\">10.5281/zenodo.3361436</a></html></td><td style=\"text-align:left;\">Presentation on pre-print versioning from Europe PMC given at the FREYA RDA UK Workshop, 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361435\">10.5281/zenodo.3361435</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>. Preprints and literature provenance in Europe PMC. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361435\">10.5281/zenodo.3361435</a></html></td><td style=\"text-align:left;\">Presentation on pre-print versioning from Europe PMC given at the FREYA RDA UK Workshop, 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361512\">10.5281/zenodo.3361512</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-6884-9970\">Brown, Christopher</a>. RDA Europe Update. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361512\">10.5281/zenodo.3361512</a></html></td><td style=\"text-align:left;\">Update presentation on the activities of RDA Europe from the RDA UK FREYA workshop on 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361511\">10.5281/zenodo.3361511</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-6884-9970\">Brown, Christopher</a>. RDA Europe Update. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361511\">10.5281/zenodo.3361511</a></html></td><td style=\"text-align:left;\">Update presentation on the activities of RDA Europe from the RDA UK FREYA workshop on 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361399\">10.5281/zenodo.3361399</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-6884-9970\">Brown, Christopher</a>. JISC and PIDs. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361399\">10.5281/zenodo.3361399</a></html></td><td style=\"text-align:left;\">Presentation outlining JISC's work relating to different persistent identifiers. Presented at the joint FREYA RDA UK Node Workshop 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361398\">10.5281/zenodo.3361398</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-6884-9970\">Brown, Christopher</a>. JISC and PIDs. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361398\">10.5281/zenodo.3361398</a></html></td><td style=\"text-align:left;\">Presentation outlining JISC's work relating to different persistent identifiers. Presented at the joint FREYA RDA UK Node Workshop 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361420\">10.5281/zenodo.3361420</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-3467-5690\">Bunakov, Vasily</a>. STFC case study: PhD research graph. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361420\">10.5281/zenodo.3361420</a></html></td><td style=\"text-align:left;\">Presentation on an STFC example of a graph created to discover relationships between PhD metadata. Presented at the RDA UK FREYA workshop, 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361419\">10.5281/zenodo.3361419</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-3467-5690\">Bunakov, Vasily</a>. STFC case study: PhD research graph. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361419\">10.5281/zenodo.3361419</a></html></td><td style=\"text-align:left;\">Presentation on an STFC example of a graph created to discover relationships between PhD metadata. Presented at the RDA UK FREYA workshop, 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361404\">10.5281/zenodo.3361404</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. RDA Open Science Graphs for FAIR Data Interest Group. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361404\">10.5281/zenodo.3361404</a></html></td><td style=\"text-align:left;\">Presentation on the proposed RDA Interest Group Open Science Graphs for FAIR Data. Presented at the RDA UK Node FREYA workshop on 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361405\">10.5281/zenodo.3361405</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. RDA Open Science Graphs for FAIR Data Interest Group. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361405\">10.5281/zenodo.3361405</a></html></td><td style=\"text-align:left;\">Presentation on the proposed RDA Interest Group Open Science Graphs for FAIR Data. Presented at the RDA UK Node FREYA workshop on 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361407\">10.5281/zenodo.3361407</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-3629-1383\">Cope, Jez</a>. DataCite in the UK. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361407\">10.5281/zenodo.3361407</a></html></td><td style=\"text-align:left;\">Presentation on DataCite services in the UK provided by the British Library. Presented at a joint RDA UK node FREYA workshop on 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361406\">10.5281/zenodo.3361406</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-3629-1383\">Cope, Jez</a>. DataCite in the UK. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361406\">10.5281/zenodo.3361406</a></html></td><td style=\"text-align:left;\">Presentation on DataCite services in the UK provided by the British Library. Presented at a joint RDA UK node FREYA workshop on 16 July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361413\">10.5281/zenodo.3361413</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-0902-4386\">Demeranville, Tom</a>. ORCID Update - RDA UK/FREYA Workshop. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361413\">10.5281/zenodo.3361413</a></html></td><td style=\"text-align:left;\">Presentation on ORCID developments in 2019 from the RDA UK/FREYA Workshop in July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3361412\">10.5281/zenodo.3361412</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-07-16</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-0902-4386\">Demeranville, Tom</a>. ORCID Update - RDA UK/FREYA Workshop. 2019-07-16; Available from: <a href=\"https://doi.org/10.5281/zenodo.3361412\">10.5281/zenodo.3361412</a></html></td><td style=\"text-align:left;\">Presentation on ORCID developments in 2019 from the RDA UK/FREYA Workshop in July 2019.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3462141\">10.5281/zenodo.3462141</a></html></td><td style=\"text-align:left;\">Project deliverable</td><td style=\"text-align:left;\">2019-08-31</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0003-4277-7988\">Mayville, Louise</a>; <a href=\"https://orcid.org/0000-0001-6660-6214\">Cousijn, Helena</a>; <a href=\"https://orcid.org/0000-0001-6899-760X\">Horik, René Van</a>; <a href=\"https://orcid.org/0000-0001-6843-7960\">Kotarski, Rachael</a>. Deliverable 5.4 Initial Training Materials. 2019-08-31; Available from: <a href=\"https://doi.org/10.5281/zenodo.3462141\">10.5281/zenodo.3462141</a></html></td><td style=\"text-align:left;\">This interim report describes the approach taken to creating training materials in the FREYA project and provides an overview of the materials created and links to them. Up to this point in the...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3462140\">10.5281/zenodo.3462140</a></html></td><td style=\"text-align:left;\">Project deliverable</td><td style=\"text-align:left;\">2019-08-31</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0003-4277-7988\">Mayville, Louise</a>; <a href=\"https://orcid.org/0000-0001-6660-6214\">Cousijn, Helena</a>; <a href=\"https://orcid.org/0000-0001-6899-760X\">Horik, René Van</a>; <a href=\"https://orcid.org/0000-0001-6843-7960\">Kotarski, Rachael</a>. Deliverable 5.4 Initial Training Materials. 2019-08-31; Available from: <a href=\"https://doi.org/10.5281/zenodo.3462140\">10.5281/zenodo.3462140</a></html></td><td style=\"text-align:left;\">This interim report describes the approach taken to creating training materials in the FREYA project and provides an overview of the materials created and links to them. Up to this point in the...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3460655\">10.5281/zenodo.3460655</a></html></td><td style=\"text-align:left;\">General</td><td style=\"text-align:left;\">2019-09-25</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0003-2883-0906\">Kearney, Nicole</a>; <a href=\"https://orcid.org/0000-0003-0557-1155\">Boruta, Luc</a>; <a href=\"https://orcid.org/0000-0001-7460-7794\">Marín-Arraiza, Paloma</a>. Fourth FREYA Ambassador Webinar. 2019-09-25; Available from: <a href=\"https://doi.org/10.5281/zenodo.3460655\">10.5281/zenodo.3460655</a></html></td><td style=\"text-align:left;\">Agenda Nicole Kearney, Biodiversity Heritage Library - What are we ‘DOI’ng about the out-of-copyright literature Luc Boruta, Thunken - Cobaltmetrics: Better a URL Today Than a PID Tomorrow Paloma...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3460654\">10.5281/zenodo.3460654</a></html></td><td style=\"text-align:left;\">General</td><td style=\"text-align:left;\">2019-09-25</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0003-2883-0906\">Kearney, Nicole</a>; <a href=\"https://orcid.org/0000-0003-0557-1155\">Boruta, Luc</a>; <a href=\"https://orcid.org/0000-0001-7460-7794\">Marín-Arraiza, Paloma</a>. Fourth FREYA Ambassador Webinar. 2019-09-25; Available from: <a href=\"https://doi.org/10.5281/zenodo.3460654\">10.5281/zenodo.3460654</a></html></td><td style=\"text-align:left;\">Agenda Nicole Kearney, Biodiversity Heritage Library - What are we ‘DOI’ng about the out-of-copyright literature Luc Boruta, Thunken - Cobaltmetrics: Better a URL Today Than a PID Tomorrow Paloma...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3514573\">10.5281/zenodo.3514573</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-10-21</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. The FREYA project: Collaborating to link people, papers, data, to new things…. 2019-10-21; Available from: <a href=\"https://doi.org/10.5281/zenodo.3514573\">10.5281/zenodo.3514573</a></html></td><td style=\"text-align:left;\"><strong>Effective scholarly research depends on collecting and linking accurate data about the varied components and outputs. Persistent identifiers (PIDs) such as ORCID IDs, DOIs, or accession...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3514572\">10.5281/zenodo.3514572</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-10-21</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. The FREYA project: Collaborating to link people, papers, data, to new things…. 2019-10-21; Available from: <a href=\"https://doi.org/10.5281/zenodo.3514572\">10.5281/zenodo.3514572</a></html></td><td style=\"text-align:left;\"><strong>Effective scholarly research depends on collecting and linking accurate data about the varied components and outputs. Persistent identifiers (PIDs) such as ORCID IDs, DOIs, or accession...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3517853\">10.5281/zenodo.3517853</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-10-24</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-4803-7411\">de Jong, Maaike</a>; <a href=\"https://orcid.org/0000-0001-6660-6214\">Cousijn, Helena</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0002-5948-0980\">Dohna, Tina</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jakobsen, Ketil</a>; <a href=\"https://orcid.org/0000-0003-3484-6875\">Garza, Kristian</a>. Project FREYA: Connecting Open Knowledge in the European Open Science Cloud - Materials. 2019-10-24; Available from: <a href=\"https://doi.org/10.5281/zenodo.3517853\">10.5281/zenodo.3517853</a></html></td><td style=\"text-align:left;\">Materials from the FREYA event Project FREYA: Connecting Open Knowledge in the European Open Science Cloud held on 21 October 2019 co-located with RDA P14 in Helsinki, Finland. Materials include...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3517852\">10.5281/zenodo.3517852</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-10-24</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-4803-7411\">de Jong, Maaike</a>; <a href=\"https://orcid.org/0000-0001-6660-6214\">Cousijn, Helena</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0002-5948-0980\">Dohna, Tina</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jakobsen, Ketil</a>; <a href=\"https://orcid.org/0000-0003-3484-6875\">Garza, Kristian</a>. Project FREYA: Connecting Open Knowledge in the European Open Science Cloud - Materials. 2019-10-24; Available from: <a href=\"https://doi.org/10.5281/zenodo.3517852\">10.5281/zenodo.3517852</a></html></td><td style=\"text-align:left;\">Materials from the FREYA event Project FREYA: Connecting Open Knowledge in the European Open Science Cloud held on 21 October 2019 co-located with RDA P14 in Helsinki, Finland. Materials include...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3554196\">10.5281/zenodo.3554196</a></html></td><td style=\"text-align:left;\">Report</td><td style=\"text-align:left;\">2019-04-28</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>; <a href=\"https://orcid.org/0000-0002-1611-6935\">McEntyre, Johanna</a>; <a href=\"https://orcid.org/0000-0002-0353-2702\">Hendricks, Ginny</a>; <a href=\"https://orcid.org/0000-0002-5948-0980\">Dohna, Tina</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jakobsen, Ketil</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0002-6137-2348\">Dallmeier-Tiessen, Sunje</a>; <a href=\"https://orcid.org/0000-0002-9576-1974\">Sandt, Stephanie Van De</a>; <a href=\"https://orcid.org/0000-0001-5633-2459\">Lavasa, Artemis</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0003-3467-5690\">Bunakov, Vasily</a>; <a href=\"https://orcid.org/0000-0002-4695-7874\">Dasler, Robin</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. Deliverable D3.2 Requirements for Selected New PID Services. 2019-04-28; Available from: <a href=\"https://doi.org/10.5281/zenodo.3554196\">10.5281/zenodo.3554196</a></html></td><td style=\"text-align:left;\">A comprehensive analysis of user stories relating to a range of entities needing persistent identifiers, with conclusions for further work in the FREYA project. The deliverable was updated after...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3554255\">10.5281/zenodo.3554255</a></html></td><td style=\"text-align:left;\">Project deliverable</td><td style=\"text-align:left;\">2019-10-18</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>; <a href=\"None\">McEntrye, Jo</a>; <a href=\"https://orcid.org/0000-0003-3467-5690\">Bunakov, Vasily</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-9576-1974\">Sandt, Stephanie Van Der</a>; <a href=\"https://orcid.org/0000-0001-6843-7960\">Kotarski, Rachael</a>; <a href=\"https://orcid.org/0000-0002-9465-4042\">Stewart, Sarah</a>; <a href=\"None\">MacEwan, Andrew</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0002-9300-5278\">Cruse, Patricia</a>; <a href=\"https://orcid.org/0000-0001-6899-760X\">Horik, René Van</a>; <a href=\"https://orcid.org/0000-0002-5948-0980\">Dohna, Tina</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jacobsen, Ketil</a>; <a href=\"https://orcid.org/0000-0002-1900-4162\">Schindler, Uwe</a>; <a href=\"None\">McCafferty, Siobhan</a>. D3.1Survey of Current PID Services Landscape - Revised. 2019-10-18; Available from: <a href=\"https://doi.org/10.5281/zenodo.3554255\">10.5281/zenodo.3554255</a></html></td><td style=\"text-align:left;\">A comprehensive survey of the landscape of persistent identifiers across many disciplines is presented, with assessments of maturity of different PID types and conclusions for the future. [Revised...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3554254\">10.5281/zenodo.3554254</a></html></td><td style=\"text-align:left;\">Project deliverable</td><td style=\"text-align:left;\">2019-10-18</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>; <a href=\"None\">McEntrye, Jo</a>; <a href=\"https://orcid.org/0000-0003-3467-5690\">Bunakov, Vasily</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-9576-1974\">Sandt, Stephanie Van Der</a>; <a href=\"https://orcid.org/0000-0001-6843-7960\">Kotarski, Rachael</a>; <a href=\"https://orcid.org/0000-0002-9465-4042\">Stewart, Sarah</a>; <a href=\"None\">MacEwan, Andrew</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0002-9300-5278\">Cruse, Patricia</a>; <a href=\"https://orcid.org/0000-0001-6899-760X\">Horik, René Van</a>; <a href=\"https://orcid.org/0000-0002-5948-0980\">Dohna, Tina</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jacobsen, Ketil</a>; <a href=\"https://orcid.org/0000-0002-1900-4162\">Schindler, Uwe</a>; <a href=\"None\">McCafferty, Siobhan</a>. D3.1Survey of Current PID Services Landscape - Revised. 2019-10-18; Available from: <a href=\"https://doi.org/10.5281/zenodo.3554254\">10.5281/zenodo.3554254</a></html></td><td style=\"text-align:left;\">A comprehensive survey of the landscape of persistent identifiers across many disciplines is presented, with assessments of maturity of different PID types and conclusions for the future. [Revised...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3564210\">10.5281/zenodo.3564210</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-12-05</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-8314-7582\">Morselli, Francesca</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0001-7785-9604\">Burton, Kath</a>; <a href=\"https://orcid.org/0000-0002-5044-5038\">Blaney, Jonathan</a>. (Effectively) Communicating your research online presentations. 2019-12-05; Available from: <a href=\"https://doi.org/10.5281/zenodo.3564210\">10.5281/zenodo.3564210</a></html></td><td style=\"text-align:left;\">Presentations from the event (Effectively) Communicating your research online, held on 4 December 2019 at the Foundling Museum in London, UK. The event, aimed at early career researchers and PhD...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3564209\">10.5281/zenodo.3564209</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2019-12-05</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-8314-7582\">Morselli, Francesca</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0001-7785-9604\">Burton, Kath</a>; <a href=\"https://orcid.org/0000-0002-5044-5038\">Blaney, Jonathan</a>. (Effectively) Communicating your research online presentations. 2019-12-05; Available from: <a href=\"https://doi.org/10.5281/zenodo.3564209\">10.5281/zenodo.3564209</a></html></td><td style=\"text-align:left;\">Presentations from the event (Effectively) Communicating your research online, held on 4 December 2019 at the Foundling Museum in London, UK. The event, aimed at early career researchers and PhD...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3585742\">10.5281/zenodo.3585742</a></html></td><td style=\"text-align:left;\">Preprint</td><td style=\"text-align:left;\">2019-12-19</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-4981-2870\">Bangert, Daniel</a>; <a href=\"None\">Hermans, Emilie</a>; <a href=\"https://orcid.org/0000-0001-6899-760X\">van Horik, René</a>; <a href=\"https://orcid.org/0000-0003-4803-7411\">de Jong, Maaike</a>; <a href=\"https://orcid.org/0000-0001-6538-7590\">Koers, Hylke</a>; <a href=\"https://orcid.org/0000-0002-0925-7983\">Mokrane, Mustapha</a>. Recommendations for Services in a FAIR data ecosystem. 2019-12-19; Available from: <a href=\"https://doi.org/10.5281/zenodo.3585742\">10.5281/zenodo.3585742</a></html></td><td style=\"text-align:left;\">This report highlights common challenges and priorities, and proposes a set of initial recommendations on how existing data infrastructures can evolve and collaborate to provide services that...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3585741\">10.5281/zenodo.3585741</a></html></td><td style=\"text-align:left;\">Preprint</td><td style=\"text-align:left;\">2019-12-19</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-4981-2870\">Bangert, Daniel</a>; <a href=\"None\">Hermans, Emilie</a>; <a href=\"https://orcid.org/0000-0001-6899-760X\">van Horik, René</a>; <a href=\"https://orcid.org/0000-0003-4803-7411\">de Jong, Maaike</a>; <a href=\"https://orcid.org/0000-0001-6538-7590\">Koers, Hylke</a>; <a href=\"https://orcid.org/0000-0002-0925-7983\">Mokrane, Mustapha</a>. Recommendations for Services in a FAIR data ecosystem. 2019-12-19; Available from: <a href=\"https://doi.org/10.5281/zenodo.3585741\">10.5281/zenodo.3585741</a></html></td><td style=\"text-align:left;\">This report highlights common challenges and priorities, and proposes a set of initial recommendations on how existing data infrastructures can evolve and collaborate to provide services that...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3631166\">10.5281/zenodo.3631166</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2020-01-30</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6383-7148\">Braukmann, Ricarda</a>; <a href=\"https://orcid.org/0000-0001-6660-6214\">Cousijn, Helena</a>; <a href=\"None\">Lammey, Rachael</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"None\">Meadows, Alice</a>. PIDforum.org - A global discussion platform about PIDs. 2020-01-30; Available from: <a href=\"https://doi.org/10.5281/zenodo.3631166\">10.5281/zenodo.3631166</a></html></td><td style=\"text-align:left;\">Presentation and discussion on pidforum.org - the global discussion platform for all things PID-related held at PIDapalooza 2020.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3631167\">10.5281/zenodo.3631167</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2020-01-30</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6383-7148\">Braukmann, Ricarda</a>; <a href=\"https://orcid.org/0000-0001-6660-6214\">Cousijn, Helena</a>; <a href=\"None\">Lammey, Rachael</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"None\">Meadows, Alice</a>. PIDforum.org - A global discussion platform about PIDs. 2020-01-30; Available from: <a href=\"https://doi.org/10.5281/zenodo.3631167\">10.5281/zenodo.3631167</a></html></td><td style=\"text-align:left;\">Presentation and discussion on pidforum.org - the global discussion platform for all things PID-related held at PIDapalooza 2020.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3632730\">10.5281/zenodo.3632730</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2020-01-31</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>. Making connections beyond papers, people, data (www.europepmc.org). 2020-01-31; Available from: <a href=\"https://doi.org/10.5281/zenodo.3632730\">10.5281/zenodo.3632730</a></html></td><td style=\"text-align:left;\">A talk demonstrating a selection PID services at Europe PMC that connect up resources in new ways and link to resources that are currently emerging with their own bespoke PIDs such as grants and...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3632729\">10.5281/zenodo.3632729</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2020-01-31</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-9317-6819\">Ferguson, Christine</a>. Making connections beyond papers, people, data (www.europepmc.org). 2020-01-31; Available from: <a href=\"https://doi.org/10.5281/zenodo.3632729\">10.5281/zenodo.3632729</a></html></td><td style=\"text-align:left;\">A talk demonstrating a selection PID services at Europe PMC that connect up resources in new ways and link to resources that are currently emerging with their own bespoke PIDs such as grants and...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3674733\">10.5281/zenodo.3674733</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2020-02-19</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0003-3629-1383\">Cope, Jez</a>; <a href=\"None\">Ashton, Jan</a>. Building the Picture behind a Dataset. 2020-02-19; Available from: <a href=\"https://doi.org/10.5281/zenodo.3674733\">10.5281/zenodo.3674733</a></html></td><td style=\"text-align:left;\">Slides from a presentation at IDCC20, Building the Picture behind a Dataset, which describes an experiment to enhance provenance information of datasets using persistent identifiers in the...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3759090\">10.5281/zenodo.3759090</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2020-04-21</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6383-7148\">Braukmann, Ricarda</a>; <a href=\"https://orcid.org/0000-0002-4695-7874\">Dasler, Robin</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jakobsen, Ketil</a>. RDC Webinar: The PID Graph and its Potential: Extending PIDs for Research Data - Presentations. 2020-04-21; Available from: <a href=\"https://doi.org/10.5281/zenodo.3759090\">10.5281/zenodo.3759090</a></html></td><td style=\"text-align:left;\">The Persistent Identifiers (PID) Graph provides a great example of the potential of persistent identifiers. Developed through the FREYA project, the PID Graph provides a way to connect and...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3759089\">10.5281/zenodo.3759089</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2020-04-21</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6383-7148\">Braukmann, Ricarda</a>; <a href=\"https://orcid.org/0000-0002-4695-7874\">Dasler, Robin</a>; <a href=\"https://orcid.org/0000-0002-1540-6594\">Koop-Jakobsen, Ketil</a>. RDC Webinar: The PID Graph and its Potential: Extending PIDs for Research Data - Presentations. 2020-04-21; Available from: <a href=\"https://doi.org/10.5281/zenodo.3759089\">10.5281/zenodo.3759089</a></html></td><td style=\"text-align:left;\">The Persistent Identifiers (PID) Graph provides a great example of the potential of persistent identifiers. Developed through the FREYA project, the PID Graph provides a way to connect and...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5438/yfck-mv39\">10.5438/yfck-mv39</a></html></td><td style=\"text-align:left;\">BlogPosting</td><td style=\"text-align:left;\">2020-05-06</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>. Powering the PID Graph: announcing the DataCite GraphQL API. 2020-05-06; Available from: <a href=\"https://doi.org/10.5438/yfck-mv39\">10.5438/yfck-mv39</a></html></td><td style=\"text-align:left;\">Today DataCite launches a new API that powers the PID Graph, the graph formed by scholarly resources described by persistent identifiers (PIDs) and the connections between them. The API is powered...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3801815\">10.5281/zenodo.3801815</a></html></td><td style=\"text-align:left;\">Poster</td><td style=\"text-align:left;\">2020-05-06</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6383-7148\">Braukmann, Ricarda</a>. The PID Forum. 2020-05-06; Available from: <a href=\"https://doi.org/10.5281/zenodo.3801815\">10.5281/zenodo.3801815</a></html></td><td style=\"text-align:left;\">This poster presents pidforum.org, a global information and discussion platform about persistent identifiers (PIDs).</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3817563\">10.5281/zenodo.3817563</a></html></td><td style=\"text-align:left;\">General</td><td style=\"text-align:left;\">2020-05-08</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-4695-7874\">Dasler, Robin</a>. FREYA PID Graph Demo. 2020-05-08; Available from: <a href=\"https://doi.org/10.5281/zenodo.3817563\">10.5281/zenodo.3817563</a></html></td><td style=\"text-align:left;\">Introductory video on the PID Graph being developed by the FREYA project. Submitted for the EOSC-hub Week 2020.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3862655\">10.5281/zenodo.3862655</a></html></td><td style=\"text-align:left;\">General</td><td style=\"text-align:left;\">2020-05-28</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>; <a href=\"https://orcid.org/0000-0001-6899-760X\">van Horik, René</a>; <a href=\"https://orcid.org/0000-0002-9576-1974\">van de Sandt, Stephanie</a>; <a href=\"https://orcid.org/0000-0001-5633-2459\">Lavasa, Artemis</a>; <a href=\"https://orcid.org/0000-0001-6660-6214\">Cousijn, Helena</a>. Guides to Choosing Persistent Identifiers - Version 1. 2020-05-28; Available from: <a href=\"https://doi.org/10.5281/zenodo.3862655\">10.5281/zenodo.3862655</a></html></td><td style=\"text-align:left;\">The FREYA Project has compiled short guides to help with choosing persistent identifiers for various types of entities. These first versions have been released in May 2020 for community feedback...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3875046\">10.5281/zenodo.3875046</a></html></td><td style=\"text-align:left;\">Presentation</td><td style=\"text-align:left;\">2020-02-18</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-4695-7874\">, Dasler</a>. Harnessing the Power of the PID Graph. 2020-02-18; Available from: <a href=\"https://doi.org/10.5281/zenodo.3875046\">10.5281/zenodo.3875046</a></html></td><td style=\"text-align:left;\">Demonstration of the FREYA PID Graph and the DataCite GraphQL API that were presented at IDCC2020 in the \"Data publishing &amp; preservation demonstrations\" session.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.5281/zenodo.3876248\">10.5281/zenodo.3876248</a></html></td><td style=\"text-align:left;\">Poster</td><td style=\"text-align:left;\">2020-05-18</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-7368-180X\">Llinares, Bernal</a>; <a href=\"https://orcid.org/0000-0003-4392-2198\">Gómez, Ferrer</a>; <a href=\"https://orcid.org/0000-0002-5355-2576\">, Wimalaratne</a>; <a href=\"None\">Juty</a>; <a href=\"https://orcid.org/0000-0001-8479-0262\">, Hermjakob</a>. Compact Identifiers Service in the Cloud. 2020-05-18; Available from: <a href=\"https://doi.org/10.5281/zenodo.3876248\">10.5281/zenodo.3876248</a></html></td><td style=\"text-align:left;\">Identifiers.org has established itself as a stable system for identification and citation of life science data, using Persistent Identifiers (PIDs). Identifiers.org not only enables researchers to...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.25495/yw94-sp56\">10.25495/yw94-sp56</a></html></td><td style=\"text-align:left;\">PID Service</td><td style=\"text-align:left;\">2020</td><td style=\"text-align:left;\"><a href=\"https://ror.orghttps://ror.org/04wxnsj81\">DataCite</a>. PID Services Registry. 2020; Available from: <a href=\"https://doi.org/10.25495/yw94-sp56\">10.25495/yw94-sp56</a></html></td><td style=\"text-align:left;\">This registry provides an overview of services related to Persistent Identifiers (PIDs). The PID Services Registry is maintained by DataCite and was developed within the European Commission-funded...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.25495/xkya-0g76\">10.25495/xkya-0g76</a></html></td><td style=\"text-align:left;\">PID Service</td><td style=\"text-align:left;\">2020</td><td style=\"text-align:left;\"><a href=\"https://ror.orghttps://ror.orghttps://ror.org/04wxnsj81\">DataCite</a>. DataCite GraphQL API; Querying the PID Graph. 2020; Available from: <a href=\"https://doi.org/10.25495/xkya-0g76\">10.25495/xkya-0g76</a></html></td><td style=\"text-align:left;\">The DataCite GraphQL API support queries of the DataCite API using the GraphQL query language. DataCite DOIs describe resources such as datasets, samples, software, and publications with rich...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.25495/x8j5-z806\">10.25495/x8j5-z806</a></html></td><td style=\"text-align:left;\">PID Service</td><td style=\"text-align:left;\">2019</td><td style=\"text-align:left;\"><a href=\"https://ror.orghttps://ror.org/04wxnsj81\">DataCite</a>. DataCite DOI Provenance API. 2019; Available from: <a href=\"https://doi.org/10.25495/x8j5-z806\">10.25495/x8j5-z806</a></html></td><td style=\"text-align:left;\">Metadata provenance is describing the history of a particular DataCite DOI metadata record, i.e. what changes were made when and by whom. This information is stored and provided via an API for all...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.25495/sh9r-dm82\">10.25495/sh9r-dm82</a></html></td><td style=\"text-align:left;\">PID Service</td><td style=\"text-align:left;\">2005</td><td style=\"text-align:left;\"><a href=\"https://ror.orghttps://ror.org/032e6b942\">Alfred Wegener Institute For Polar And Marine Research</a>; <a href=\"https://ror.orghttps://ror.org/02gn1ar53\">Marum</a>. PANGAEA; Data Publisher for Earth &amp; Environmental Science. 2005; Available from: <a href=\"https://doi.org/10.25495/sh9r-dm82\">10.25495/sh9r-dm82</a></html></td><td style=\"text-align:left;\">The information system PANGAEA is operated as an Open Access library aimed at archiving, publishing and distributing georeferenced data from earth system research. The system guarantees long-term...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.25495/fxd6-ba56\">10.25495/fxd6-ba56</a></html></td><td style=\"text-align:left;\">PID Service</td><td style=\"text-align:left;\">2019</td><td style=\"text-align:left;\"><a href=\"https://ror.orghttps://ror.org/008pnp284\">Data Archiving And Networked Services</a>; <a href=\"https://ror.orghttps://ror.org/05dhe8b71\">British Library</a>; <a href=\"https://ror.orghttps://ror.org/04wxnsj81\">DataCite</a>. The PID Forum. 2019; Available from: <a href=\"https://doi.org/10.25495/fxd6-ba56\">10.25495/fxd6-ba56</a></html></td><td style=\"text-align:left;\">The PID Forum is a global information and discussion platform about persistent identifiers (PIDs). The PID Forum aims to bring together the various communities working with PIDs in the research...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.14454/r0ed-fh20\">10.14454/r0ed-fh20</a></html></td><td style=\"text-align:left;\">Computational Notebook</td><td style=\"text-align:left;\">2020-05-08</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6333-2182\">Petryszak, Robert</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-7368-180X\">Llinares, Manuel Bernal</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. FREYA PID Graph - Datacenter Publication Citations. 2020-05-08; Available from: <a href=\"https://doi.org/10.14454/r0ed-fh20\">10.14454/r0ed-fh20</a></html></td><td style=\"text-align:left;\">Jupyter notebook that uses GraphQL to implement EC-funded FREYA Project User Story 1: As a data center, I want to see the citations of publications that use my repository for the underlying data,...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.14454/qaym-kt26\">10.14454/qaym-kt26</a></html></td><td style=\"text-align:left;\">Computational Notebook</td><td style=\"text-align:left;\">2020-05-10</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6333-2182\">Petryszak, Robert</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-7368-180X\">Llinares, Manuel Bernal</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. FREYA PID Graph - Grant Outputs. 2020-05-10; Available from: <a href=\"https://doi.org/10.14454/qaym-kt26\">10.14454/qaym-kt26</a></html></td><td style=\"text-align:left;\">Jupyter notebook that uses GraphQL to implement EC-funded FREYA Project User Story 10: As a funder, we want to be able to find all the outputs related to our awarded grants, including block grants...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.14454/27b7-9g84\">10.14454/27b7-9g84</a></html></td><td style=\"text-align:left;\">Computational Notebook</td><td style=\"text-align:left;\">2020-06-01</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6333-2182\">Petryszak, Robert</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-7368-180X\">Llinares, Manuel Bernal</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. FREYA PID Graph - Software Citations. 2020-06-01; Available from: <a href=\"https://doi.org/10.14454/27b7-9g84\">10.14454/27b7-9g84</a></html></td><td style=\"text-align:left;\">Jupyter notebook that uses GraphQL to implement EC-funded FREYA Project User Story 2: As a software author, I want to be able to see the citations of my software aggregated across all versions. so...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.14454/jkar-xj80\">10.14454/jkar-xj80</a></html></td><td style=\"text-align:left;\">Computational Notebook</td><td style=\"text-align:left;\">2020-05-19</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6333-2182\">Petryszak, Robert</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-7368-180X\">Llinares, Manuel Bernal</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. FREYA PID Graph - Dissertations. 2020-05-19; Available from: <a href=\"https://doi.org/10.14454/jkar-xj80\">10.14454/jkar-xj80</a></html></td><td style=\"text-align:left;\">Jupyter notebook that uses GraphQL to implement EC-funded FREYA Project User Story 5: As a student using the British Library's EThOS database, I want to be able to find all dissertations on a given...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.14454/62t3-0822\">10.14454/62t3-0822</a></html></td><td style=\"text-align:left;\">Computational Notebook</td><td style=\"text-align:left;\">2020-05-25</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6333-2182\">Petryszak, Robert</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-7368-180X\">Llinares, Manuel Bernal</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. FREYA PID Graph - Researcher Co-authors. 2020-05-25; Available from: <a href=\"https://doi.org/10.14454/62t3-0822\">10.14454/62t3-0822</a></html></td><td style=\"text-align:left;\">Jupyter notebook that uses GraphQL to implement EC-funded FREYA Project User Story 9: As a bibliometrician, I want to know all the co-authors of a particular researcher, so that I can do a network...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.14454/y785-xs19\">10.14454/y785-xs19</a></html></td><td style=\"text-align:left;\">Computational Notebook</td><td style=\"text-align:left;\">2020-05-24</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6333-2182\">Petryszak, Robert</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-7368-180X\">Llinares, Manuel Bernal</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. FREYA PID Graph - Impacts of Data. 2020-05-24; Available from: <a href=\"https://doi.org/10.14454/y785-xs19\">10.14454/y785-xs19</a></html></td><td style=\"text-align:left;\">Jupyter notebook that uses GraphQL to implement EC-funded FREYA Project User Story 8: As a longitudinal study, I want to be able to deduplicate the metrics/impact for our data, so that I can see...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.14454/fqq6-w751\">10.14454/fqq6-w751</a></html></td><td style=\"text-align:left;\">Collection</td><td style=\"text-align:left;\">2020-05-08</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0001-6333-2182\">Petryszak, Robert</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0001-9570-8121\">Lambert, Simon</a>; <a href=\"https://orcid.org/0000-0002-7368-180X\">Llinares, Manuel Bernal</a>; <a href=\"https://orcid.org/0000-0002-5432-6116\">Madden, Frances</a>. FREYA PID Graph Jupyter Notebooks. 2020-05-08; Available from: <a href=\"https://doi.org/10.14454/fqq6-w751\">10.14454/fqq6-w751</a></html></td><td style=\"text-align:left;\">Jupyter notebooks that use GraphQL to implement EC-funded FREYA Project PID Graph user stories.</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr><tr><td style=\"text-align:left;\"><a href=\"https://doi.org/10.14454/e0f7-zs08\">10.14454/e0f7-zs08</a></html></td><td style=\"text-align:left;\">SoftwareSourceCode</td><td style=\"text-align:left;\">2020-06-26</td><td style=\"text-align:left;\"><a href=\"https://orcid.org/0000-0002-8599-0773\">Hallett, Richard</a>; <a href=\"https://orcid.org/0000-0003-1419-2405\">Fenner, Martin</a>; <a href=\"https://orcid.org/0000-0003-0618-1722\">Fokianos, Pamfilos</a>. Beagle: the code for the FREYA PID Services Registry. 2020-06-26; Available from: <a href=\"https://doi.org/10.14454/e0f7-zs08\">10.14454/e0f7-zs08</a></html></td><td style=\"text-align:left;\">The FREYA project is building up human and technical resources to support persistent identifier (PID) infrastructure in the European Open Science Cloud (EOSC). One important gap identified during...</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td><td style=\"text-align:left;\">0</td></tr></table></html>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import display, HTML\n",
    "import textwrap\n",
    "xstr = lambda s: 'General' if s is None else str(s)\n",
    "\n",
    "# Get details for each output\n",
    "outputs = [['ID','Type','Publication Date','Formatted Citation','Descriptions', 'Number of Citations', 'Number of Views', 'Number of Downloads']]\n",
    "# Since there is scope for duplicates in Zenodo, versions of previously seen nodes are considered duplicates and stored in duplicate_versions so that \n",
    "# they can be excluded if seen later\n",
    "for r in funder['nodes']:\n",
    "    id = '<a href=\"%s\">%s</a></html>' % (r['id'], '/'.join(r['id'].split(\"/\")[3:]))\n",
    "    if r['versionOfCount'] > 0:\n",
    "        # If the current output is a version of another one, exclude it\n",
    "        continue\n",
    "    # As Publication Date, pick out date of type: 'Issued'; failing that use 'Created' date.\n",
    "    pub_date = None\n",
    "    for date_dict in r['dates']:\n",
    "        if pub_date is None:\n",
    "            if date_dict['dateType'] in ['Issued', 'Created']:\n",
    "                pub_date = date_dict['date'];\n",
    "        else:\n",
    "            if date_dict['dateType'] in ['Issued']:\n",
    "                pub_date = date_dict['date'];\n",
    "    \n",
    "    titles = '; '.join([s['title'] for s in r['titles']])\n",
    "    creators = '; '.join(['<a href=\"%s\">%s</a>' % (s['id'],s['name']) for s in r['creators']])\n",
    "    formatted_citation = \"%s. %s. %s; Available from: %s\" % (creators, titles, pub_date, id) \n",
    "    resource_type = xstr(r['types']['resourceType'])\n",
    "    descriptions = textwrap.shorten('; '.join([s['description'] for s in r['descriptions']]), width=200, placeholder=\"...\")\n",
    "    output = [id, resource_type, pub_date, formatted_citation, descriptions, str(r['citationCount']), str(r['viewCount']), str(r['downloadCount'])]\n",
    "    outputs += [output]\n",
    "    \n",
    "# Display outputs as html table \n",
    "html_table = '<html><table>'   \n",
    "html_table += '<tr><th style=\"text-align:center;\">' + '</th><th style=\"text-align:center;\">'.join(outputs[0]) + '</th></tr>'\n",
    "for row in outputs[1:]:\n",
    "    html_table += '<tr><td style=\"text-align:left;\">' + '</td><td style=\"text-align:left;\">'.join(row) + '</td></tr>'\n",
    "html_table += '</table></html>'\n",
    "display(HTML(html_table))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot number of outputs per resource type\n",
    "Plot as a pie chart the number of [FREYA grant award](https://cordis.europa.eu/project/id/777523) outputs per resource type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d94f588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot as a pie chart the number of outputs per resource type\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import FormatStrFormatter\n",
    "import numpy as np\n",
    "import operator\n",
    "\n",
    "xstr = lambda s: 'General' if s is None else str(s)\n",
    "\n",
    "plt.rcdefaults()\n",
    "\n",
    "# Retrieve works counts by resource type from nodes\n",
    "# Pick out date of type: 'Issued'; failing that use 'Created' date.\n",
    "funder = data['funder']['works']\n",
    "num_outputs_dict = {}\n",
    "for r in funder['nodes']:\n",
    "    resource_type = xstr(r['types']['resourceType'])\n",
    "    if resource_type not in num_outputs_dict:\n",
    "        num_outputs_dict[resource_type] = 0\n",
    "    num_outputs_dict[resource_type] += 1;\n",
    "    \n",
    "# Sort resource types by count of work desc\n",
    "sorted_num_outputs = sorted(num_outputs_dict.items(),key=operator.itemgetter(1),reverse=True)\n",
    "# Populate lists needed for pie chart\n",
    "resource_types = [s[0] for s in sorted_num_outputs] \n",
    "num_outputs = [s[1] for s in sorted_num_outputs] \n",
    "\n",
    "# Generate a pie chart of number of grant outputs by resource type\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0,0,1,1])\n",
    "ax.set_title('Number of Grant Outputs per Resource Type')\n",
    "ax.axis('equal')\n",
    "ax.pie(num_outputs, labels = resource_types,autopct='%1.2f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display an interactive plot of co-authorship relationships across all outputs\n",
    "Display an interactive chord plot representing co-authorship relationships across all [FREYA grant award](https://cordis.europa.eu/project/id/777523) outputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"1000\"\n",
       "            height=\"1000\"\n",
       "            src=\"./out.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x1223ba828>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate a Chord plot representing co-authorship relationships across all grant award outputs\n",
    "from chord import Chord       \n",
    "from IPython.display import IFrame\n",
    "\n",
    "all_creator_names_by_node = []\n",
    "all_creator_names_set = set([])\n",
    "funder = data['funder']['works']\n",
    "for r in funder['nodes']:\n",
    "    if r['versionOfCount'] > 0:\n",
    "        # If the current output is a version of another one, exclude it\n",
    "        continue\n",
    "    # To minimise cropping of names in the below, retain just the first letter of the first name\n",
    "    # if the author name is well formatted     \n",
    "    creator_names = []\n",
    "    for name in [s['name'] for s in r['creators'] if s['name']]:\n",
    "        if name.find(\",\") > 0:\n",
    "            creator_names.append(name[0:name.index(\",\") + 3])\n",
    "        elif name.find(\",\") == 0:\n",
    "            creator_names.append(name[1:].strip())\n",
    "        else:\n",
    "            creator_names.append(name)\n",
    "    all_creator_names_by_node.append(creator_names)\n",
    "    all_creator_names_set.update(creator_names)\n",
    "    \n",
    "# Assemble data structures for the co-authorship chord diagram\n",
    "all_creator_names = sorted(list(all_creator_names_set))\n",
    "\n",
    "# Initialise chord data matrix\n",
    "length = len(all_creator_names)\n",
    "coauthorship_matrix = []\n",
    "for i in range(length):\n",
    "    r = []\n",
    "    for j in range(length):\n",
    "        r.append(0)\n",
    "    coauthorship_matrix.append(r)\n",
    "    \n",
    "# Populate chord data matrix\n",
    "for node_creators in all_creator_names_by_node:\n",
    "    for creator in node_creators:\n",
    "        c_pos = all_creator_names.index(creator)\n",
    "        for co_creator in node_creators:\n",
    "            co_pos = all_creator_names.index(co_creator)\n",
    "            if c_pos != co_pos:\n",
    "                coauthorship_matrix[c_pos][co_pos] += 1\n",
    "\n",
    "# display co-authorship cord diagram\n",
    "plot = Chord(coauthorship_matrix, all_creator_names, padding=0.04, wrap_labels=False, margin=130, width=1000).to_html()\n",
    "IFrame(src=\"./out.html\", width=1000, height=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot number of outputs per license type\n",
    "Plot as a pie chart the number of [FREYA grant award](https://cordis.europa.eu/project/id/777523) outputs per license type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11dd32cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot as a pie chart the number of outputs per license type\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import FormatStrFormatter\n",
    "import numpy as np\n",
    "import operator\n",
    "\n",
    "xstr = lambda s: 'General' if s is None else str(s)\n",
    "xstr1 = lambda s: 'Not available' if s is None else str(s)\n",
    "\n",
    "plt.rcdefaults()\n",
    "\n",
    "# Retrieve works counts by resource type from nodes\n",
    "funder = data['funder']\n",
    "awardTitle = None\n",
    "\n",
    "right2NumOutputs = {}\n",
    "resourceType2NumOutputs = {}\n",
    "\n",
    "for r in funder['works']['nodes']:\n",
    "    resourceType = xstr(r['types']['resourceType'])\n",
    "    if r['versionOfCount'] > 0:\n",
    "        # If the current output is a version of another one, exclude it\n",
    "        continue\n",
    "    if not awardTitle:\n",
    "        awardTitle = r['fundingReferences'][0]['awardTitle'] \n",
    "    if resourceType not in resourceType2NumOutputs:\n",
    "        resourceType2NumOutputs[resourceType] = 0\n",
    "    resourceType2NumOutputs[resourceType] += 1\n",
    "    if not r['rights']:\n",
    "        r['rights'].append({'rights': 'Not available'})\n",
    "    for rights in r['rights']:\n",
    "        right = xstr1(rights['rights'])\n",
    "        if right not in right2NumOutputs:\n",
    "            right2NumOutputs[right] = 0\n",
    "        right2NumOutputs[right] += 1;\n",
    "    \n",
    "# Sort resource types by count of work desc\n",
    "sorted_num_outputs = sorted(right2NumOutputs.items(),key=operator.itemgetter(1),reverse=True)\n",
    "# Populate lists needed for pie chart\n",
    "resource_types = [s[0] for s in sorted_num_outputs] \n",
    "num_outputs = [s[1] for s in sorted_num_outputs] \n",
    "\n",
    "# Generate a pie chart of number of grant outputs by resource type\n",
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0,0,1,1])\n",
    "ax.set_title('Number of Grant Outputs per License Type')\n",
    "ax.axis('equal')\n",
    "ax.pie(num_outputs, labels = resource_types,autopct='%1.2f%%')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot license type counts per resources type\n",
    "Plot stacked bar plot showing how <ins>each type</ins> of [FREYA grant award](https://cordis.europa.eu/project/id/777523) outputs contributes their license type counts to the corresponding aggregated total.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "License Types of European Commission's [FREYA grant award](https://cordis.europa.eu/project/id/777523) outputs, shown per output type as a stacked bar plot:"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"500\"\n",
       "            height=\"500\"\n",
       "            src=\"./out1.html\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x11d1d8588>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import plotly.io as pio\n",
    "import plotly.express as px\n",
    "from IPython.display import IFrame\n",
    "import pandas as pd\n",
    "from operator import itemgetter\n",
    "\n",
    "xstr = lambda s: 'General' if s is None else str(s)\n",
    "xstr1 = lambda s: 'Not available' if s is None else str(s)\n",
    "\n",
    "# Adapted from: https://stackoverflow.com/questions/58766305/is-there-any-way-to-implement-stacked-or-grouped-bar-charts-in-plotly-express\n",
    "def px_stacked_bar(df, color_name='License Type', y_name='Metrics', **pxargs):\n",
    "    idx_col = df.index.name\n",
    "    m = pd.melt(df.reset_index(), id_vars=idx_col, var_name=color_name, value_name=y_name)\n",
    "    # For Plotly colour sequences see: https://plotly.com/python/discrete-color/     \n",
    "    return px.bar(m, x=idx_col, y=y_name, color=color_name, **pxargs, \n",
    "                  color_discrete_sequence=px.colors.qualitative.Pastel1)\n",
    " \n",
    "# Collect metric counts\n",
    "funder = data['funder']\n",
    "funderName = funder['name']\n",
    "\n",
    "# Initialise dicts for the stacked bar plot\n",
    "labels = {0: 'All Output Types'}\n",
    "\n",
    "# Map each license type to a dict in turn mapping the position of the output's bar in plot \n",
    "# to the count of outputs corresponding to that license type\n",
    "licenseType2Pos2Count = {}\n",
    "\n",
    "# Collect output type labels and assign bar positions in plot\n",
    "outputType2Pos = {}\n",
    "pos = 1\n",
    "for outputType, num in sorted(resourceType2NumOutputs.items(), key = itemgetter(1), reverse = True):\n",
    "    labels[pos] = outputType\n",
    "    outputType2Pos[outputType] = pos\n",
    "    pos += 1\n",
    "    \n",
    "# Populate license type counts per output type (key = i) and add them to the aggregated counts (key: 0)\n",
    "for node in funder['works']['nodes']:\n",
    "    if node['versionOfCount'] > 0:\n",
    "        # If the current output is a version of another one, exclude it\n",
    "        continue       \n",
    "    resource_type = xstr(node['types']['resourceType'])\n",
    "    pos = outputType2Pos[resource_type]\n",
    "    if len(node['rights']) == 0:\n",
    "        node['rights'].append({'rights': 'Not available'})\n",
    "    for rights in node['rights']:\n",
    "        right = xstr1(rights['rights'])\n",
    "        if right not in licenseType2Pos2Count:\n",
    "            licenseType2Pos2Count[right] = {}\n",
    "            for pos1, _ in enumerate(labels):\n",
    "                # Initialise right's counts for each output type\n",
    "                licenseType2Pos2Count[right][pos1] = 0\n",
    "        licenseType2Pos2Count[right][0] += 1 \n",
    "        licenseType2Pos2Count[right][pos] += 1\n",
    "        \n",
    "# Create stacked bar plot\n",
    "x_name = \"Output Types (sorted by number of outputs)\"\n",
    "dfDict = {x_name: labels}\n",
    "\n",
    "for right in licenseType2Pos2Count:\n",
    "    dfDict[right] = licenseType2Pos2Count[right]\n",
    "\n",
    "df = pd.DataFrame(dfDict)\n",
    "fig = px_stacked_bar(df.set_index(x_name), y_name = \"Output Counts\")\n",
    "\n",
    "# Set plot background to transparent\n",
    "fig.update_layout({\n",
    "'plot_bgcolor': 'rgba(0, 0, 0, 0)',\n",
    "'paper_bgcolor': 'rgba(0, 0, 0, 0)'\n",
    "})\n",
    "\n",
    "# Write interactive plot out to html file\n",
    "pio.write_html(fig, file='out1.html')\n",
    "\n",
    "# Display plot from the saved html file\n",
    "display(Markdown(\"License Types of %s's [FREYA grant award](https://cordis.europa.eu/project/id/777523) outputs, shown per output type as a stacked bar plot:\" % funderName))\n",
    "IFrame(src=\"./out1.html\", width=500, height=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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