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https://github.com/UB-Mannheim/FAIR-Data-Week

FAIR Data Week at Uni Mannheim
https://github.com/UB-Mannheim/FAIR-Data-Week

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FAIR Data Week at Uni Mannheim

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README 

        
# FAIR-Data-Week



FAIR Data Week is a recurrent event at University of Mannheim with introductory talks about the FAIR principles. FAIR means **F**indable, **A**ccessible, **I**nteroperable and **R**eusable.



**Organizer**: [Research Data Center](https://www.bib.uni-mannheim.de/lehren-und-forschen/forschungsdatenzentrum) at [Mannheim University Library](https://www.bib.uni-mannheim.de) of the [University of Mannheim](https://www.uni-mannheim.de)



**Instructor**: [Renat Shigapov](https://www.bib.uni-mannheim.de/ihre-ub/ansprechpersonen/dr-renat-shigapov)



**Dates & Time**: 30.05.2023-02.06.2023 & Wed 12:30 pm - 12:50 pm



**Location**: Zoom



The first [FAIR Data Week](https://www.bib.uni-mannheim.de/lehren-und-forschen/forschungsdatenzentrum/fair-data-week):



| Title        | Date           | Time  | DOI  |

| ------------- |:-------------:| -----:| -----:|

| FAIR Data Week: F for Findable      | 30.05.2023 | 12:30-12:50 pm | [10.5281/zenodo.7984881](https://doi.org/10.5281/zenodo.7984881) |

| FAIR Data Week: A for Accessible      | 31.05.2023 | 12:30-12:50 pm | [10.5281/zenodo.7989605](https://doi.org/10.5281/zenodo.7989605) |

| FAIR Data Week: I for Interoperable     | 01.06.2023 | 12:30-12:50 pm | [10.5281/zenodo.7993735](https://doi.org/10.5281/zenodo.7993735)  |

| FAIR Data Week: R for Reusable     | 02.06.2023 | 12:30-12:50 pm | [10.5281/zenodo.7997250](https://doi.org/10.5281/zenodo.7997250)  |



**Useful resources on the FAIR principles**:



* European Commission, Directorate-General for Research and Innovation, "Turning FAIR into reality" – Final report and action plan from the European Commission expert group on FAIR data, Publications Office, 2018, https://data.europa.eu/doi/10.2777/1524

* [Guidelines on FAIR Data Management in Horizon 2020](https://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf)

* [FAIR principles at GO FAIR](https://www.go-fair.org/fair-principles)

* [OpenAIRE Guide for Researchers "How to make your data FAIR”](https://www.openaire.eu/how-to-make-your-data-fair)

* [How to FAIR](https://www.howtofair.dk)

* [FAIRdata Forum](https://fairdataforum.org)

* FAIR courses:

   * [Course "Open and FAIR research data"](https://www.fosteropenscience.eu/node/2820)

   * [Course "Assessing the FAIRness of data"](https://www.fosteropenscience.eu/node/2644)

* [FAIR Nanopublications](https://github.com/peta-pico/fair-nanopubs)

   * [FAIR Vocabulary](https://peta-pico.github.io/FAIR-nanopubs/principles/index-en.html)

   * [FAIR Implementation Profile (FIP) Ontology](https://peta-pico.github.io/FAIR-nanopubs/fip/index-en.html)

   * [FAIR Implementation Choices and Challenges Model](https://peta-pico.github.io/FAIR-nanopubs/icc/index-en.html)

* FAIR assessment resources:

   * [F-UJI Automated FAIR Data Assessment Tool](https://www.f-uji.net)

   * Lang, Kevin, Assmann, Cora, Neute, Nadine, Gerlach, Roman, & Rex, Jessica. (2023). FAIR Assessment Tools Overview (2.1). 3. Sächsische FDM-Tagung, Leipzig. Zenodo. https://doi.org/10.5281/zenodo.7701941

   * Jones, Sarah, & Grootveld, Marjan. (2017, November 24). How FAIR are your data?. Zenodo. https://doi.org/10.5281/zenodo.1065991

   * [FAIR Data Self Assessment Tool](https://ardc.edu.au/resource/fair-data-self-assessment-tool)



## FAIR Data Week: F for Findable



* [F1: (Meta)data are assigned a globally unique and persistent identifier](https://www.go-fair.org/fair-principles/f1-meta-data-assigned-globally-unique-persistent-identifiers)

* [F2: Data are described with rich metadata ](https://www.go-fair.org/fair-principles/f2-data-described-rich-metadata)

* [F3: Metadata clearly and explicitly include the identifier of the data they describe](https://www.go-fair.org/fair-principles/f3-metadata-clearly-explicitly-include-identifier-data-describe)

* [F4: (Meta)data are registered or indexed in a searchable resource](https://www.go-fair.org/fair-principles/f4-metadata-registered-indexed-searchable-resource)



**Idea**: Metadata and data shall be findable by both humans and machines.



**Motivation**: to prevent data loss, to (re)use data, to acknowledge the owner(s) by citing the data, to enable reproducibility of research, to increase the visibility of research.



**How to make your data findable?** 

* Deposit your data to a data repository. Check out your institutional repo and domain-specific repos. Registries of data repositories are:

   * https://www.re3data.org 

   * https://fairsharing.org 

* Publish a data paper in a data journal. A list of data journals:

   * https://www.forschungsdaten.org/index.php/Data_Journals 

* Advertise your data via conferences, social media and collaborations



**Useful Resources**



* [Findability in the FAIR Cookbook for FAIR Doers from ELIXIR Europe](https://faircookbook.elixir-europe.org/content/recipes/findability)



## FAIR Data Week: A for Accessible



* [A1: (Meta)data are retrievable by their identifier using a standardised communication protocol](https://www.go-fair.org/fair-principles/metadata-retrievable-identifier-standardised-communication-protocol)

   * [A1.1: The protocol is open, free and universally implementable](https://www.go-fair.org/fair-principles/a1-1-protocol-open-free-universally-implementable)

   * [A1.2: The protocol allows for an authentication and authorisation procedure where necessary](https://www.go-fair.org/fair-principles/a1-2-protocol-allows-authentication-authorisation-required)

* [A2: Metadata should be accessible even when the data is no longer available](https://www.go-fair.org/fair-principles/a2-metadata-accessible-even-data-no-longer-available)



**Idea**: A user needs to know how data can be accessed, possibly including authentication and authorisation. Authentication verifies the identity of a user. Authorization gives those users permission to access a resource.



**Motivation**: to prevent data loss, to prevent unauthorised access, to enable authorised access, to enable data (re)use, to enable reproducibility of research, to increase the visibility of research.



**How to make your data accessible?** 



* Deposit your data to a data repository. Describe accessibility conditions of data. Registries of data repositories are:

   * https://www.re3data.org 

   * https://fairsharing.org 

* In case of sensitive data, delegate accessibility issues to a research data center:

   * [research data centers accredited by the German Data Forum (RatSWD)](https://www.konsortswd.de/en/datacentres/all-datacentres)

   * [research data centers at Universities in Germany, Austria and Switzerland](https://www.forschungsdaten.org/index.php/FDM-Kontakte)

* Publish a data paper in a data journal. Describe accessibility conditions of data. A list of data journals:

   * https://www.forschungsdaten.org/index.php/Data_Journals

* Advertise your data and describe accessibility conditions



**Useful Resources**



* [Accessibility in the FAIR Cookbook for FAIR Doers from ELIXIR Europe](https://faircookbook.elixir-europe.org/content/recipes/accessibility)



## FAIR Data Week: I for Interoperable



* [I1: (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation](https://www.go-fair.org/fair-principles/i1-metadata-use-formal-accessible-shared-broadly-applicable-language-knowledge-representation)

* [I2: (Meta)data use vocabularies that follow the FAIR principles](https://www.go-fair.org/fair-principles/i2-metadata-use-vocabularies-follow-fair-principles)

* [I3: (Meta)data include qualified references to other (meta)data](https://www.go-fair.org/fair-principles/i3-metadata-include-qualified-references-metadata)



**Idea**: Interoperability is ability to exchange metadata and data with various agents (humans, machines, institutions, organizations and countries). Metadata and data are easy to integrate with other (meta)data and to use with different software and workflows.



**Motivation**: to exchange metadata and data, to improve trust and communication, to enable (meta)data (re)use, to enable reproducibility of research, to increase the visibility of research.



**How to make your data interoperable?** 



* Find a data repository, where you can specify the metadata using the vocabularies which follow the FAIR principles. Registries of data repositories are:

   * https://www.re3data.org 

   * https://fairsharing.org 

* Add references to other data into your metadata, use standard data formats and deposit your data to the data repository

* Upload metadata for your data to interoperable general-purpose or domain-specific knowledge graphs:

   * https://www.wikidata.org

* Advertise your data with references to other (meta)data



**Useful Resources**



* [Interoperability in the FAIR Cookbook for FAIR Doers from ELIXIR Europe](https://faircookbook.elixir-europe.org/content/recipes/interoperability)



## FAIR Data Week: R for Reusable



* [R1: (Meta)data are richly described with a plurality of accurate and relevant attributes](https://www.go-fair.org/fair-principles/r1-metadata-richly-described-plurality-accurate-relevant-attributes)

   * [R1.1: (Meta)data are released with a clear and accessible data usage license](https://www.go-fair.org/fair-principles/r1-1-metadata-released-clear-accessible-data-usage-license)

   * [R1.2: (Meta)data are associated with detailed provenance](https://www.go-fair.org/fair-principles/r1-2-metadata-associated-detailed-provenance)

   * [R1.3: (Meta)data meet domain-relevant community standards](https://www.go-fair.org/fair-principles/r1-3-metadata-meet-domain-relevant-community-standards)



**Idea**: Metadata and data should be well-described so that they can be used, replicated and combined in different settings.



**Motivation**: to facilitate collaborations and further research, to acknowledge the owner(s) by citing it, to enable reproducibility of research, to increase the visibility of research



**How to make your data reusable?**



* Deposit your data to a data repository. Describe as much metadata as possible following the community standards and include a license. Registries of data repositories are:

   * https://www.re3data.org 

   * https://fairsharing.org 

* Publish a data paper in a data journal. Describe as much metadata as possible following the community standards and include a license. A list of data journals:

   * https://www.forschungsdaten.org/index.php/Data_Journals 

* Advertise your data attaching as much metadata as possible following the community standards and include a license 



**Useful Resources**



* [Reusability in the FAIR Cookbook for FAIR Doers from ELIXIR Europe](https://faircookbook.elixir-europe.org/content/recipes/reusability)