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MovingPandas: Software Submission for Review #18

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anitagraser opened this issue Jan 6, 2020 · 72 comments
Open

MovingPandas: Software Submission for Review #18

anitagraser opened this issue Jan 6, 2020 · 72 comments
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@anitagraser
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@anitagraser anitagraser commented Jan 6, 2020

Submitting Author: Anita Graser (@anitagraser)
Package Name: MovingPandas
One-Line Description of Package: Trajectory classes and functions built on top of GeoPandas
Repository Link: https://github.com/anitagraser/movingpandas
Version submitted: 0.2
Editor: Jenny Palomino (@jlpalomino)
Reviewer 1: Ivan Ogasawara (@xmnlab)
Reviewer 2: Martin Fleischmann (@martinfleis)
Archive: TBD
Version accepted: TBD


Description

  • Include a brief paragraph describing what your package does:

MovingPandas is a package for dealing with movement data. MovingPandas implements a Trajectory class and corresponding methods based on GeoPandas. A trajectory has a time-ordered series of point geometries. These points and associated attributes are stored in a GeoDataFrame. MovingPandas implements spatial and temporal data access and analysis functions (covered in the open access publication [0]) as well as plotting functions.
A usage example is available at http://exploration.movingpandas.org,

[0] Graser, A. (2019). MovingPandas: Efficient Structures for Movement Data in Python. GI_Forum ‒ Journal of Geographic Information Science 2019, 1-2019, 54-68. doi:10.1553/giscience2019_01_s54. URL: https://www.austriaca.at/rootcollection?arp=0x003aba2b

Scope

  • Please indicate which category or categories this package falls under:
    • Data retrieval
    • Data extraction
    • Data munging
    • Data deposition
    • Reproducibility
    • Geospatial
    • Education
    • Data visualization*

* Please fill out a pre-submission inquiry before submitting a data visualization package. For more info, see this section of our guidebook.

  • Explain how the and why the package falls under these categories (briefly, 1-2 sentences):

Geospatial (primary): The MovingPandas Trajectory class implements is a spatio-temporal data model for movement data.

Data visualization (secondary): The implemented plot functions enable straight-forward movement data exploration that goes beyond plotting the individual point locations by ensuring that trajectories are represented by linear segments between consecutive points.

  • Who is the target audience and what are scientific applications of this package?

Movement data / trajectories appear in many different scientific domains, including physics, biology, ecology, chemistry, transport and logistics, astrophysics, remote sensing, and more.
For example, the provided tutorials cover the analysis of migrating birds as well as the analysis of ship movement within a port.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?

scikit-mobility is a similar package which is also in an early development stage and also deals with movement data. They implement TrajectoryDataFrames and FlowDataFrames on top of Pandas instead of GeoPandas. There is little overlap in the covered use cases and implemented functionality (comparing MovingPandas tutorials and scikit-mobility tutorials). MovingPandas focuses on spatio-temporal data exploration with corresponding functions for data manipulation and analysis. scikit-mobility on the other hand focuses on computing human mobility metrics, generating synthetic trajectories and assessing privacy risks.

  • If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:

#14

Technical checks

For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:

  • does not violate the Terms of Service of any service it interacts with.
  • has an OSI approved license
  • contains a README with instructions for installing the development version.
  • includes documentation with examples for all functions.
  • contains a vignette (notebook) with examples of its essential functions and uses.
  • has a test suite.
  • has continuous integration, such as Travis CI, AppVeyor, CircleCI, and/or others.

Publication options

JOSS Checks
  • The package has an obvious research application according to JOSS's definition in their submission requirements. Be aware that completing the pyOpenSci review process does not guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS.
  • The package is not a "minor utility" as defined by JOSS's submission requirements: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria.
  • The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
  • The package is deposited in a long-term repository with the DOI:

Note: Do not submit your package separately to JOSS

Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?

This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.

  • Yes I am OK with reviewers submitting requested changes as issues to my repo. Reviewers will then link to the issues in their submitted review.

Code of conduct

P.S. Have feedback/comments about our review process? Leave a comment here

Editor and Review Templates

Editor and review templates can be found here

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@lwasser lwasser commented Jan 15, 2020

hi @anitagraser !! thank you again for this submission. it will be on our discussion list for this thursday's pyopensci meeting! can you think of any folks who might be well suited to review this package? we will need 2 people.

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@anitagraser anitagraser commented Jan 15, 2020

Thank you @lwasser! I think GeoPandas developers would be a good fit.

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@lwasser lwasser commented Jan 16, 2020

@jlpalomino will be the fearless editor for this submission !! And @xmnlab will be our first reviewer. We will reach out to the geopandas folks. @martinfleis would you be interested in being a second reviewer for moving pandas? please let us know!

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@martinfleis martinfleis commented Jan 16, 2020

@lwasser I would love to do that, but not sure how fast I'd be. What is the timeframe?

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@lwasser lwasser commented Jan 16, 2020

hey @martinfleis we understand. we typically ask for a 3 week turn around on reviews. Would that timeframe work for you or is that too quick? Many thanks for responding so quickly!

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@martinfleis martinfleis commented Jan 16, 2020

@lwasser that seems to be doable. Count me in.

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@lwasser lwasser commented Jan 17, 2020

awesome!! Thanks @martinfleis for doing this!!

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@jlpalomino jlpalomino commented Jan 17, 2020

Editor checks:

  • Fit: The package meets criteria for fit and overlap.
  • Automated tests: Package has a testing suite and is tested via Travis-CI or another CI service.
  • License: The package has an OSI accepted license
  • Repository: The repository link resolves correctly
  • Archive (JOSS only, may be post-review): The repository DOI resolves correctly
  • Version (JOSS only, may be post-review): Does the release version given match the GitHub release (v1.0.0)?

Editor comments

Thanks @xmnlab and @martinfleis for agreeing to review MovingPandas. Please use the following resources to submit your review:

The submitting author is open to receiving issues and PRs if you want to create a review using that approach (e.g. include links to the issue and/or PR in your review).

Feel free to reach out with any questions about the review process.


Reviewers: Ivan Ogasawara (@xmnlab) and Martin Fleischmann (@martinfleis)
Due date: February 7th, 2020

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@martinfleis martinfleis commented Jan 28, 2020

Package Review

  • As the reviewer I confirm that there are no conflicts of interest for me to review this work (If you are unsure whether you are in conflict, please speak to your editor before starting your review).

Documentation

The package includes all the following forms of documentation:

  • A statement of need clearly stating problems the software is designed to solve and its target audience in README

  • Installation instructions: for the development version of package and any non-standard dependencies in README

  • Vignette(s) demonstrating major functionality that runs successfully locally

  • Function Documentation: for all user-facing functions

    • The documentation is not ideal as there are often missing explanations of options for string inputs of available methods, like in Trajectory.get_position_at() or Trajectory.generalize(). I would personally also prefer having one place with all documentation sources, or at least links between them. Some parts are in Readme, some in examples and other on RTD.
  • Examples for all user-facing functions

    • The repository contains extraordinary Jupyter Notebooks working as a user guide and new are being created. All run locally as well as on mybinder if one wants to play with the data quickly. However, there is no link to all the examples apart from my binder badge. One has to find them in the repository.

    • Minor typo in 3_horse_collar.ipynb: ha is 10 000 not 1 000 m (which is correct at another place).: total_area = total_area[collar_id]/1000

  • Community guidelines including contribution guidelines in the README or CONTRIBUTING.

    • Contribution guidelines seem to be missing. I haven't found them anywhere.
  • Metadata including author(s), author e-mail(s), a url, and any other relevant metadata e.g., in a setup.py file or elsewhere.

Readme requirements
The package meets the readme requirements below:

  • Package has a README.md file in the root directory.

The README should include, from top to bottom:

  • The package name

  • Badges for continuous integration and test coverage, the badge for pyOpenSci peer-review once it has started (see below), a repostatus.org badge, and any other badges. If the README has many more badges, you might want to consider using a table for badges, see this example, that one and that one. Such a table should be more wide than high.

    • Code coverage is missing, pyOpenSci peer-review is missing, repostatus.org badge is missing.
  • Short description of goals of package, with descriptive links to all vignettes (rendered, i.e. readable, cf the documentation website section) unless the package is small and there’s only one vignette repeating the README.

  • Installation instructions

  • Any additional setup required (authentication tokens, etc)

  • Brief demonstration usage

  • Direction to more detailed documentation (e.g. your documentation files or website).

  • If applicable, how the package compares to other similar packages and/or how it relates to other packages

  • Citation information

    • There are references to related papers, but it is not clear how should be movingpandas itself cited.

Functionality

  • Installation: Installation succeeds as documented.

  • Functionality: Any functional claims of the software been confirmed.

  • Performance: Any performance claims of the software been confirmed.

  • Automated tests: Tests cover essential functions of the package and a reasonable range of inputs and conditions. All tests pass on the local machine.

    • I'd say that the essential functions are covered, but the overall coverage could be higher. E.g. movingpandas/trajectory_collection.py is covered only from 63%. I am aware that movingpandas/trajectory_aggregator.py is new so I assume that its tests are still TBD.
Name                                               Stmts   Miss  Cover
----------------------------------------------------------------------
movingpandas/__init__.py                               6      0   100%
movingpandas/geometry_utils.py                        45      4    91%
movingpandas/overlay.py                              152     12    92%
movingpandas/tests/__init__.py                         0      0   100%
movingpandas/tests/test_geometry_utils.py             41      0   100%
movingpandas/tests/test_overlay.py                    78      0   100%
movingpandas/tests/test_trajectory.py                208      0   100%
movingpandas/tests/test_trajectory_collection.py      54      0   100%
movingpandas/trajectory.py                           298     29    90%
movingpandas/trajectory_aggregator.py                229    192    16%
movingpandas/trajectory_collection.py                113     42    63%
movingpandas/trajectory_plotter.py                    82     13    84%
----------------------------------------------------------------------
TOTAL                                               1306    292    78%
  • Continuous Integration: Has continuous integration, such as Travis CI, AppVeyor, CircleCI, and/or others.

    • I would recommend adding one testing environment with dev versions of key packages (geopandas, shapely) to check for the potential issues with new versions soon enough to fix them. Testing under Windows (e.g. AppVeyor) could also be helpful as there are differences in the behaviour of Python geospatial stack between OS.
  • Packaging guidelines: The package conforms to the pyOpenSci packaging guidelines.

For packages co-submitting to JOSS

Note: Be sure to check this carefully, as JOSS's submission requirements and scope differ from pyOpenSci's in terms of what types of packages are accepted.

The package contains a paper.md matching JOSS's requirements with:

  • A short summary describing the high-level functionality of the software
  • Authors: A list of authors with their affiliations
  • A statement of need clearly stating problems the software is designed to solve and its target audience.
  • References: with DOIs for all those that have one (e.g. papers, datasets, software).

Final approval (post-review)

  • The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Estimated hours spent reviewing: 5


Review Comments

MovingPandas is a valuable addition to python geospatial stack. Being built on top of GeoPandas GeoDataFrames, its main classes are easy to understand, and the whole work with MovingPandas is very natural and straightforward. I had almost no issues in using it with my data, and everything works as advertised.

Initially, I was a bit confused by released versions of MovingPandas as when I started there was no release on GitHub and PyPI had different version than conda-forge. I would recommend following JOSS recommendation here and trying to keep these 3 (GitHub, PyPI, conda-forge) in sync as GitHub releases automatically send a notification to watching users.

During the review process, I have opened a couple of issues/PRs in the original repository, all linked above this post.

I am excited to see the further development of it as the latest addition of trajectory aggregator looks brilliant. I will certainly follow new releases, and once I have to work with movement data, MovingPandas will be the first choice.

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@anitagraser anitagraser commented Jan 29, 2020

Thanks a lot for the thorough review and great feedback, Martin! I'll work on the open issues.

I've been looking for the badge for pyOpenSci peer-review but haven't been able to locate one for ongoing peer review.

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@martinfleis martinfleis commented Jan 29, 2020

I've been looking for the badge for pyOpenSci peer-review but haven't been able to locate one for ongoing peer review.

That is more the question for @lwasser and @jlpalomino, I just copied review template.

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@jlpalomino jlpalomino commented Jan 29, 2020

Thanks @martinfleis for your review.

@anitagraser I also was not able to find the badge details in our review guide, so I have made a note to look into where we provide this info.

Here is the badge for pyOpenSci peer review, with the second link being the URL to this issue:
[![pyOpenSci](https://tinyurl.com/y22nb8up)](https://github.com/pyOpenSci/software-review/issues/18)

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@anitagraser anitagraser commented Jan 30, 2020

If fixed the remaining README issues: badges anitagraser/movingpandas#53 and citation information anitagraser/movingpandas@56ef608

The last open issue from Martin's review should be the Contribution guidelines.

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@xmnlab xmnlab commented Jan 30, 2020

I am planning to review MovingPandas today :)

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@anitagraser anitagraser commented Jan 30, 2020

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@lwasser lwasser commented Jan 31, 2020

@anitagraser when your package has fully passed both reviews and both reviewers are happy with your addressing their requested changes, we will ask you to add the badge to the readme!! please get in touch with any other questions. @martinfleis THANK YOU for this review!!

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@lwasser lwasser commented Jan 31, 2020

one other question @anitagraser are you interested in JOSS? i see you didn't check the box. Joss only requires you to write a very short paper about the package (i can show you the earthpy example) . They accept the pyopensci technical review by default. no worries if you are not interested... but it's a nice citation to have if you are (linked to your orcid id and such).

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@anitagraser anitagraser commented Jan 31, 2020

@lwasser Thank you. Do I understand correctly that I should remove the pyopensci badge from the MovingPandas readme again? Is there a different badge to fulfill the requirement in the review template "the badge for pyOpenSci peer-review once it has started"?

Concerning JOSS, I have been thinking about it but wasn't sure if JOSS sees prior publications as an obstacle:

Graser, A. (2019). MovingPandas: Efficient Structures for Movement Data in Python. GI_Forum ‒ Journal of Geographic Information Science 2019, 1-2019, 54-68. doi:10.1553/giscience2019_01_s54. URL: https://www.austriaca.at/rootcollection?arp=0x003aba2b

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@anitagraser anitagraser commented Jan 31, 2020

@lwasser After looking at the earthpy paper you mentioned, I think there should be minimal overlap with the existing MovingPandas paper in GI_Forum. So yes, I'd like to try a JOSS submission.

Work in progress: https://github.com/anitagraser/movingpandas/tree/joss-paper

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@xmnlab xmnlab commented Feb 3, 2020

I will finish my review today :)

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@anitagraser anitagraser commented Mar 1, 2020

@martinfleis Right! For JOSS, I'll still have to get a DOI.

I might bump the MovingPandas version to 0.3. (Movingpandas 0.2 works for geopandas 0.6.3. MovingPandas 0.3 works with GeoPandas 0.7)

The paper is in a dedicated brach for now: https://github.com/anitagraser/movingpandas/blob/joss-paper/paper.md

Is there anything else?

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@martinfleis martinfleis commented Mar 2, 2020

I've checked the paper and there does not seem to be any issue re JOSS requirements. Just few very minor notes.

  • matplotlib reference is missing
  • after MyBinder link is missing dot
  • JOSS apparently makes a new line in the middle of code, which in some cases breaks movingpandas, geopandas, and python words. See linked pdf - paper.pdf. You can check how it renders on https://whedon.theoj.org.

I'll formally update my review post to include JOSS boxes, but I am happy with the package and all responses and recommend it for a publication on both pyOpenSci and JOSS.

anitagraser added a commit to anitagraser/movingpandas that referenced this issue Mar 2, 2020
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@anitagraser anitagraser commented Mar 7, 2020

@martinfleis Thank you for reviewing the paper! I have fixed the first two issues. I don't see how to affect the line break (third issue you mentioned) and found that this issue also appears in recently published papers, such as https://joss.theoj.org/papers/10.21105/joss.02075

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@jlpalomino jlpalomino commented Mar 9, 2020

Hi @anitagraser, it is correct that based on the recent pyOpenSci guideline discussion, examples for all user-facing functions would not be considered a requirement under the OK/Better/Best framework. For the overall review, if the reviewers felt that the OK requirements have been met and recommend accepting the package, then a package could be accepted to pyOpenSci.

For everyone - we welcome all additional comments on the OK/Better/Best framework and/or the overall acceptance process.

Thanks @martinfleis for expanding your review to include the JOSS tick boxes.

@xmnlab Can you please expand your review to address the tick boxes for the JOSS submission? The paper can be found at: https://github.com/anitagraser/movingpandas/blob/joss-paper/paper.md
Thanks!

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@xmnlab xmnlab commented Mar 9, 2020

@jlpalomino I am updating my review today and I will expand my review for JOSS submission section.

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@xmnlab xmnlab commented Mar 12, 2020

@anitagraser thanks for having working hard on all the recommendations.

MovingPandas documenation looks very good. I just found some minor issues. Some methods' docstring don't have the parameters section:

MovingPandas.TrajectoryCollection:

MovingPandas.Trajectory

I am starting to review JOSS section now. thanks again!

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@xmnlab xmnlab commented Mar 12, 2020

Some suggestions related to docstrings (not required):

  • Inside Parameters section, you can use optional and default information to add more details about the parameter, for example:
x : int, optional
    Some description of parameter `x` (the default is -1, which implies summation over all axes).

ref: https://numpydoc.readthedocs.io/en/latest/format.html

  • When a parameter can only assume one of a fixed set of values, those values can be listed in braces, with the default appearing first, for example: order : {'C', 'F', 'A'}
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@xmnlab xmnlab commented Mar 12, 2020

JOSS Review section:

It looks very good! I just noticed a minor issue, also mentioned by @martinfleis , related to some word break like GeoPandas, MovingPandas.

thanks for working on that @anitagraser , let me know if I can help in anyway.

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@anitagraser anitagraser commented Mar 14, 2020

MovingPandas documenation looks very good. I just found some minor issues. Some methods' docstring don't have the parameters section:

Thank you, @xmnlab! I've added the missing parameter sections: anitagraser/movingpandas@b98b404

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@anitagraser anitagraser commented Mar 14, 2020

And a Zenodo DOI is set up DOI

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@anitagraser anitagraser commented Mar 16, 2020

v0.3rc1 has landed on conda-forge https://anaconda.org/conda-forge/movingpandas

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@xmnlab xmnlab commented Mar 16, 2020

awesome! @anitagraser thanks for letting us know about the new release :)

Final approval (post-review)

  • The author has responded to my review and made changes to my satisfaction. I recommend approving this package.

Thanks @anitagraser for working on the recommendations and congrats for the hard work you are doing on MovingPandas!

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@jlpalomino jlpalomino commented Mar 16, 2020

Thank you @martinfleis and @xmnlab for your final reviews of MovingPandas. We also really appreciate all of your feedback on the review process.

Great work @anitagraser! Both reviewers have provided their final approvals for acceptance to pyOpenSci. I will follow up with next steps shortly. Thanks.

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@anitagraser anitagraser commented Mar 17, 2020

Thank you for all you feedback @xmnlab, much appreciated!

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@jlpalomino jlpalomino commented Mar 19, 2020

Hi @anitagraser you may have seen that I have followed up with @martinfleis to tie up loose ends related to two open issues from his review.

One item is for you is about versions. The last JOSS check for the editor is: Version (JOSS only, may be post-review): Does the release version given match the GitHub release (v1.0.0)?

It seems that there is a slight difference between the GitHub version 0.3.rc2 versus Zenodo version v0.3.rc1 and conda forge version v0.3.rc1. Please let me know if I am misinterpreting this information. Thanks!

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@anitagraser anitagraser commented Mar 19, 2020

Thank you @jlpalomino!

Concerning versions: in my experience, it is common practice to increase the version in Github immediately after a release. Think of it as a necessary step for starting work on the next release.

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@martinfleis martinfleis commented Mar 19, 2020

@jlpalomino I am happy with all changes. I thought I indicated it clearly above, but apparently not enough. There is nothing to be resolved from my side.

@anitagraser versions should be ideally in sync between GitHub, PyPI, conda-forge and zenodo.

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@anitagraser anitagraser commented Mar 19, 2020

I've reverted the version number to rc1 anitagraser/movingpandas@bba76fe

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@jlpalomino jlpalomino commented Mar 19, 2020

Thanks @martinfleis for your prompt responses about those issues (for final documentation purposes) and for your response related to the versions.

@anitagraser thanks for your action on the version. I checked in with @lwasser about the version difference as well. We have typically followed the version sync suggested by @martinfleis, that the GitHub repository remains the same version and only changes when there is a new release. However, we understand that there could be commits happening before the new release. She has suggested that we open a discussion on discourse to see what others think is best practice for versions.

That said, let's start moving forward with closing this review, while we wait for the community to weigh in. I will post a new comment with the next steps.

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@jlpalomino jlpalomino commented Mar 19, 2020

MovingPandas has been approved for pyOpenSci! Thanks @anitagraser for this submission and @martinfleis and @xmnlab for your detailed reviews!

@anitagraser Here are the next steps:

  • Add the badge for pyOpenSci peer review, with the second link being the URL to this issue:
    pyOpenSci
  • Submit a PR to pyopensci.github.io to add MovingPandas to the pyOpenSci package list and to add yourself as a contributor using:
contributor_type:
    - package-maintainer

and

packages-submitted: ["movingpandas"]

If you are interested (not required), you can write a blog post for the pyOpenSci website about MovingPandas (see blog post about pandera) to promote your package.

The last action item is for me to get the process started with JOSS, who will provide more information on their process. I will do that in a new comment.

Please feel free to let me know if you have any questions, and congrats again.

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@jlpalomino jlpalomino commented Mar 19, 2020

Hi @arfon pyOpenSci has approved MovingPandas. @anitagraser is interested in JOSS publication, and the draft paper has been reviewed by the pyOpenSci reviewers.

@anitagraser has another publication that she feels demonstrates minimal overlap:
Graser, A. (2019). MovingPandas: Efficient Structures for Movement Data in Python. GI_Forum ‒ Journal of Geographic Information Science 2019, 1-2019, 54-68. doi:10.1553/giscience2019_01_s54.

Please feel free to contact @anitagraser (or myself if needed) for any additional information needed for the JOSS review process. Thanks!

anitagraser added a commit to anitagraser/movingpandas that referenced this issue Mar 20, 2020
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@arfon arfon commented Mar 20, 2020

@anitagraser - feel free to open an issue on the JOSS repository about this paper. On initial inspection I would say that JOSS would not accept a paper about MovingPandas as the earlier publication looks to be describing essentially the same software.

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@anitagraser anitagraser commented Mar 20, 2020

Thank you for your feedback, @arfon!
As mentioned in #18 (comment), I wasn't sure if prior publications would be an obstacle. Graser (June 2019) describes the concepts underlying MovingPandas and presents an early unreleased version of the library. (The first release was published later in Sept 2019 https://pypi.org/project/movingpandas/#history.) MovingPandas has evolved considerably since then.
If you think that this is clearly against JOSS requirements, I won't pursue it further.

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@arfon arfon commented Mar 20, 2020

@anitagraser - could you summarize the major changes between MovingPandas when Graser (2019) was submitted compared to how it is today?

We do allow for multiple papers for the same piece of software but would expect at least a major release of the software to warrant an additional paper.

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@anitagraser anitagraser commented Mar 20, 2020

@arfon Thank you for the clarification!

Graser (June 2019) only describes the Trajectory class and it's data handling functions.

The key improvements since then are:

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