references.bib

@misc{hoebelheinrich_nancy_j_2022_6769695,
  author       = {Hoebelheinrich, Nancy J and
                  Biernacka, Katarzyna and
                  Brazas, Michelle and
                  Castro, Leyla Jael and
                  Fiore, Nicola and
                  Hellstrom, Margareta and
                  Lazzeri, Emma and
                  Leenarts, Ellen and
                  Martinez Lavanchy, Paula Maria and
                  Newbold, Elizabeth and
                  Nurnberger, Amy and
                  Plomp, Esther and
                  Vaira, Lucia and
                  van Gelder, Celia W G and
                  Whyte, Angus},
  title        = {{Recommendations for a minimal metadata set to aid 
                   harmonised discovery of learning resources}},
  month        = jun,
  year         = 2022,
  publisher    = {Zenodo},
  version      = {1.0},
  doi          = {10.15497/RDA00073},
  url          = {https://doi.org/10.15497/RDA00073}
}

@article{Garcia2020,
  abstract      = {Everything we do today is becoming more and more reliant on the use of computers. The field of biology is no exception; but most biologists receive little or no formal preparation for the increasingly computational aspects of their discipline. In consequence, informal training courses are often needed to plug the gaps; and the demand for such training is growing worldwide. To meet this demand, some training programs are being expanded, and new ones are being developed. Key to both scenarios is the creation of new course materials. Rather than starting from scratch, however, it's sometimes possible to repurpose materials that already exist. Yet finding suitable materials online can be difficult: They're often widely scattered across the internet or hidden in their home institutions, with no systematic way to find them. This is a common problem for all digital objects. The scientific community has attempted to address this issue by developing a set of rules (which have been called the Findable, Accessible, Interoperable and Reusable [FAIR] principles) to make such objects more findable and reusable. Here, we show how to apply these rules to help make training materials easier to find, (re)use, and adapt, for the benefit of all.},
  author        = {Garcia, Leyla and Batut, B{\'{e}}r{\'{e}}nice and Burke, Melissa L. and Kuzak, Mateusz and Psomopoulos, Fotis and Arcila, Ricardo and Attwood, Teresa K. and Beard, Niall and Carvalho-Silva, Denise and Dimopoulos, Alexandros C. and {Del Angel}, Victoria Dominguez and Dumontier, Michel and Gurwitz, Kim T. and Krause, Roland and McQuilton, Peter and {Le Pera}, Loredana and Morgan, Sarah L. and Rauste, P{\"{a}}ivi and Via, Allegra and Kahlem, Pascal and Rustici, Gabriella and {Van Gelder}, Celia W.G. and Palagi, Patricia M.},
  doi           = {10.1371/journal.pcbi.1007854},
  file          = {:Users/geertvangeest/Downloads/pcbi.1007854.pdf:pdf},
  isbn          = {1111111111},
  issn          = {15537358},
  journal       = {PLoS Computational Biology},
  number        = {5},
  pages         = {1--9},
  pmid          = {32437350},
  title         = {{Ten simple rules for making training materials FAIR}},
  volume        = {16},
  year          = {2020}
}


@misc{creative_commons_2022, 
  title={When we share, everyone wins}, 
  url={https://creativecommons.org/}, 
  publisher={Creative Commons}, 
  note = {Accessed: 2022-08-11}
} 

@misc{open-source-licenses, 
title={Open Source Licenses: Types and Comparison}, 
url={https://snyk.io/learn/open-source-licenses/}, 
publisher={Snyk}, 
note = {Accessed: 2023-02-10}
} 

@article{10.1093/bioinformatics/btt113,
    author = {Ison, Jon and Kalaš, Matúš and Jonassen, Inge and Bolser, Dan and Uludag, Mahmut and McWilliam, Hamish and Malone, James and Lopez, Rodrigo and Pettifer, Steve and Rice, Peter},
    title = "{EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats}",
    journal = {Bioinformatics},
    volume = {29},
    number = {10},
    pages = {1325-1332},
    year = {2013},
    month = {03},
    abstract = "{Motivation: Advancing the search, publication and integration of bioinformatics tools and resources demands consistent machine-understandable descriptions. A comprehensive ontology allowing such descriptions is therefore required.Results: EDAM is an ontology of bioinformatics operations (tool or workflow functions), types of data and identifiers, application domains and data formats. EDAM supports semantic annotation of diverse entities such as Web services, databases, programmatic libraries, standalone tools, interactive applications, data schemas, datasets and publications within bioinformatics. EDAM applies to organizing and finding suitable tools and data and to automating their integration into complex applications or workflows. It includes over 2200 defined concepts and has successfully been used for annotations and implementations.Availability: The latest stable version of EDAM is available in OWL format from http://edamontology.org/EDAM.owl and in OBO format from http://edamontology.org/EDAM.obo. It can be viewed online at the NCBO BioPortal and the EBI Ontology Lookup Service. For documentation and license please refer to http://edamontology.org. This article describes version 1.2 available at http://edamontology.org/EDAM\_1.2.owl.Contact: jison@ebi.ac.uk}",
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btt113},
    url = {https://doi.org/10.1093/bioinformatics/btt113},
    eprint = {https://academic.oup.com/bioinformatics/article-pdf/29/10/1325/710075/btt113.pdf},
}