Nachweise

Global Indigenous Data Alliance. CARE Principles of Indigenous Data Governance. https://www.gida-global.org/care

Schweizerischer Nationalfonds zur Förderung der wissenschaftlichen Forschung. Data Management Plan (DMP) – Leitlinien für Forschende. http://www.snf.ch/de/derSnf/forschungspolitische_positionen/open_research_data/Seiten/data-management-plan-dmp-leitlinien-fuer-forschende.aspx

Wilkinson, M. D. et al. (2016). The FAIR Guiding Principles for Scientific Data Management and Stewardship. Scientific Data, 3, Artikel 160018. https://doi.org/10.1038/sdata.2016.18


Weiterführende Literatur 

Bishop, B. W., Hank, C., Webster, J. & Howard, R. (2019). Scientists' Data Discovery and Reuse Behavior: (Meta)data Fitness for Use and the FAIR Data Principles. Proceedings of the Association for Information Science and Technology, 56(1), 21–31. https://doi.org/10.1002/pra2.4

Blaiszik, B., Chard, K., Pruyne, J., Ananthakrishnan, R., Tuecke, S. & Foster, I. (2016). The Materials Data Facility: Data Services to Advance Materials Science Research. JOM: The Journal of The Minerals, Metals & Materials Society, 68(8), 2045–2052. https://doi.org/10.1007/s11837-016-2001-3

Bloemers, M. & Montesanti, A. (2020). The FAIR Funding Model: Providing a Framework for Research Funders to Drive the Transition toward FAIR Data Management and Stewardship Practices. Data Intelligence, 2(1-2), 171–180. https://doi.org/10.1162/dint_a_00039

Boeckhout, M., Zielhuis, G. A. & Bredenoord, A. L. (2018). The FAIR Guiding Principles for Data Stewardship: Fair Enough? European Journal of Human Genetics, 26(7), 931–936. https://doi.org/10.1038/s41431-018-0160-0

Calamai, S. & Frontini, F. (2018). FAIR Data Principles and Their Application to Speech and Oral Archives. Journal of New Music Research, 47(4), 339–354. https://doi.org/10.1080/09298215.2018.1473449

Corpas, M., Kovalevskaya, N. V., McMurray, A. & Nielsen, F. G. G. (2018). A FAIR Guide for Data Providers to Maximise Sharing of Human Genomic Data. PLoS Computational Biology, 14(3), e1005873. https://doi.org/10.1371/journal.pcbi.1005873

Draxl, C. & Scheffler, M. (2018). NOMAD: The FAIR Concept for Big Data-Driven Materials Science. MRS Bulletin, 43(9), 676–682. https://doi.org/10.1557/mrs.2018.208

Evans, B., Druken, K., Wang, J., Yang, R., Richards, C. & Wyborn, L. (2017). A Data Quality Strategy to Enable FAIR, Programmatic Access across Large, Diverse Data Collections for High Performance Data Analysis. Informatics, 4(4), 45. https://doi.org/10.3390/informatics4040045

Groth, P., Cousijn, H., Clark, T. & Goble, C. (2020). FAIR Data Reuse – the Path through Data Citation. Data Intelligence, 2(1-2), 78–86. https://doi.org/10.1162/dint_a_00030

Helliwell, J. R., Minor, W., Weiss, M. S., Garman, E. F., Read, R. J., Newman, J., van Raaij, M. J., Hajdu, J. & Baker, E. N. (2019). Findable Accessible Interoperable Re-usable (FAIR) Diffraction Data Are Coming to Protein Crystallography. International Union of Crystallography Journal, 6(3), 341–343. https://doi.org/10.1107/S2052252519005918

Hiebel, G., Goldenberg, G., Grutsch, C., Hanke, K. & Staudt, M. (2020). FAIR Data for Prehistoric Mining Archaeology. International Journal on Digital Libraries, 7(1-2), 70. https://doi.org/10.1007/s00799-020-00282-8

Hunter, A. M., Carreira, E. M. & Miller, S. J. (2020). Encouraging Submission of FAIR Data at The Journal of Organic Chemistry and Organic Letters. Organic Letters, 22(4), 1231–1232. https://doi.org/10.1021/acs.orglett.0c00383

Jetten, M., Simons, E. & Rijnders, J. (2019). The Role of CRIS’s in the Research Life Cycle. A Case Study on Implementing a FAIR RDM Policy at Radboud University, the Netherlands. Procedia Computer Science, 146, 156–165. https://doi.org/10.1016/j.procs.2019.01.090

Koymans, M. R., Hinsbergen, D. J. J., Pastor‐Galán, D., Vaes, B. & Langereis, C. G. (2020). Towards FAIR Paleomagnetic Data Management through Paleomagnetism.org 2.0. Geochemistry, Geophysics, Geosystems, 21(2), 101. https://doi.org/10.1029/2019GC008838

Labastida, I. & Margoni, T. (2020). Licensing FAIR Data for Reuse. Data Intelligence, 2(1-2), 199–207. https://doi.org/10.1162/dint_a_00042

Lannom, L., Koureas, D. & Hardisty, A. R. (2020). FAIR Data and Services in Biodiversity Science and Geoscience. Data Intelligence, 2(1-2), 122–130. https://doi.org/10.1162/dint_a_00034

León, M. A. P. de & Ferrer, L. A. i. de (2018). From Open Access to Open Data: Collaborative Work in the University Libraries of Catalonia. Liber Quarterly: The Journal of the Association of European Research Libraries, 28, 1–14. https://doi.org/10.18352/lq.10253

Li, Q., García-Muelas, R. & López, N. (2018). Microkinetics of Alcohol Reforming for H2 Production from a FAIR Density Functional Theory Database. Nature Communications, 9(1), 526. https://doi.org/10.1038/s41467-018-02884-y

Liu, H., Li, X., Xu, M., Mo, R. & Ma, J. (2017). A Fair Data Access Control towards Rational Users in Cloud Storage. Information Sciences, 418-419, 258–271. https://doi.org/10.1016/j.ins.2017.07.023

Matthews, P. C. (2019). FAIR Data Needed to Liberate Hepatitis B Virus (HBV) from the Catch-22 of Neglect. Journal of Global Health, 9(1), 010310. https://doi.org/10.7189/jogh.09-010310

Mons, B. (2019). FAIR Science for Social Machines: Let's Share Metadata Knowlets in the Internet of FAIR Data and Services. Data Intelligence, 1(1), 22–42. https://doi.org/10.1162/dint_a_00002

Mons, B., Neylon, C., Velterop, J., Dumontier, M., da Silva Santos, L. O. B. & Wilkinson, M. D. (2017). Cloudy, Increasingly FAIR; Revisiting the FAIR Data Guiding Principles for the European Open Science Cloud. Information Services and Use, 37(1), 49–56. https://doi.org/10.3233/ISU-170824

Moreira, J. L. R., Bonino, L., Ferreira Pires, L., van Sinderen, M. & Henning, P. (2019). Towards Findable, Accessible, Interoperable and Reusable (FAIR) Data Repositories: Improving a Data Repository to Behave as a FAIR Data Point. Liinc em Revista, 15(2). https://doi.org/10.18617/liinc.v15i2.4817

Murphy, F. (2018). Open Access, Open Data, FAIR Data and Their Implications for Life Sciences Researchers. Emerging Topics in Life Sciences, 2(6), 759–762. https://doi.org/10.1042/ETLS20180163

o. A. (2017). Data Models to GO-FAIR. Nature Genetics, 49(7), 971. https://doi.org/10.1038/ng.3910

o. A. (2019). Announcement: FAIR Data in Earth Science. Nature, 565(7738), 134. https://doi.org/10.1038/d41586-019-00075-3

o. A. (2019). FAIR Play in Geoscience Data. Nature Geoscience, 12(12), 961. https://doi.org/10.1038/s41561-019-0506-4

Oeltjen, W., Neumann, K., Stahl, U. & Stephan, R. (2019). MyCoRe macht Forschungsdaten FAIR. Bibliothek Forschung und Praxis, 43(1), 82–90. https://doi.org/10.1515/bfp-2019-2013

Peeters, L. M. (2018). Fair Data for Next-Generation Management of Multiple Sclerosis. Multiple Sclerosis, 24(9), 1151–1156. https://doi.org/10.1177/1352458517748475

Pergl, R., Hooft, R., Suchánek, M., Knaisl, V. & Slifka, J. (2019). “Data Stewardship Wizard”: A Tool Bringing Together Researchers, Data Stewards, and Data Experts around Data Management Planning. Data Science Journal, 18(4). https://doi.org/10.5334/dsj-2019-059

Qin, J., Coll, I. S., Zeng, M. L. & Dobreski, B. (2019). Technical and Policy Underpinnings of FAIR Data Principles. Proceedings of the Association for Information Science and Technology, 56(1), 569–571. https://doi.org/10.1002/pra2.93

Rodríguez-Iglesias, A., Rodríguez-González, A., Irvine, A. G., Sesma, A., Urban, M., Hammond-Kosack, K. E. & Wilkinson, M. D. (2016). Publishing FAIR Data: An Exemplar Methodology Utilizing PHI-Base. Frontiers in Plant Science, 7, 641. https://doi.org/10.3389/fpls.2016.00641

Rychlik, M., Zappa, G., Añorga, L., Belc, N., Castanheira, I., Donard, O. F. X., Kouřimská, L., Ogrinc, N., Ocké, M. C., Presser, K. & Zoani, C. (2018). Ensuring Food Integrity by Metrology and FAIR Data Principles. Frontiers in Chemistry, 6, 49. https://doi.org/10.3389/fchem.2018.00049

Rzepa, H. (2015). A Convincing Example of the Need for Data Repositories. FAIR Data. The Winnower, 7, e142313.30279. https://doi.org/10.15200/winn.142313.30279

Schaaf, J., Kadioglu, D., Goebel, J., Behrendt, C.-A., Roos, M., van Enckevort, D., Ückert, F., Sadiku, F., Wagner, T. O. F. & Storf, H. (2018). OSSE Goes FAIR - Implementation of the FAIR Data Principles for an Open-Source Registry for Rare Diseases. Studies in Health Technology and Informatics, 253, 209–213.

Schafer, B. & Edwards, L. (2017). “I Spy, With My Little Sensor”: Fair Data Handling Practices for Robots between Privacy, Copyright and Security. Connection Science, 29(3), 200–209. https://doi.org/10.1080/09540091.2017.1318356

Simms, S. R. & Jones, S. (2017). Next-Generation Data Management Plans: Global, Machine-Actionable, FAIR. International Journal of Digital Curation, 12(1), 36–45. https://doi.org/10.2218/ijdc.v12i1.513

Stall, S., Yarmey, L., Cutcher-Gershenfeld, J., Hanson, B., Lehnert, K., Nosek, B., Parsons, M., Robinson, E. & Wyborn, L. (2019). Make Scientific Data FAIR. Nature, 570(7759), 27–29. https://doi.org/10.1038/d41586-019-01720-7

Tang, L. (2020). FAIR Your Data. Nature Methods, 17(2), 127. https://doi.org/10.1038/s41592-020-0742-y

Tanhua, T., Pouliquen, S., Hausman, J., O’Brien, K., Bricher, P., Bruin, T. de, Buck, J. J. H., Burger, E. F., Carval, T., Casey, K. S., Diggs, S., Giorgetti, A., Glaves, H., Harscoat, V., Kinkade, D., Muelbert, J. H., Novellino, A., Pfeil, B., Pulsifer, P. L., . . . Zhao, Z. (2019). Ocean FAIR Data Services. Frontiers in Marine Science, 6, 440. https://doi.org/10.3389/fmars.2019.00440

The Global Indigienous Data Alliance. (2019). CARE Principles for Indigenous Data Governance (Full). https://static1.squarespace.com/static/5d3799de845604000199cd24/t/5da9f4479ecab221ce848fb2/1571419335217/CARE+Principles_One+Pagers+FINAL_Oct_17_2019.pdf

The Global Indigienous Data Alliance. (2019). CARE Principles for Indigenous Data Governance (Summary). https://static1.squarespace.com/static/5d3799de845604000199cd24/t/5d79c383e904c741c9e9cd86/1568260995760/CARE+Principles+for+Indigenous+Data+Governance_FINAL_Sept+06+2019.pdf

United Nations. (27. November 2019). United Nations Declaration on the Rights of Indigenous Peoples. https://www.un.org/development/desa/indigenouspeoples/wp-content/uploads/sites/19/2018/11/UNDRIP_E_web.pdf

Veiga, V. S. d. O., Henning, P., Dib, S., Penedo, E., Lima, J. D. C., Silva, L. O. B. d. & Pires, L. F. (2019). Plano de Gestão de Dados FAIR: Uma Proposta Para a Fiocruz. Liinc em Revista, 15(2). https://doi.org/10.18617/liinc.v15i2.5030

Wilcox, D. (2018). Supporting FAIR Data Principles with Fedora. Liber Quarterly: The Journal of the Association of European Research Libraries, 28(1), 1-8. https://doi.org/10.18352/lq.10247

Wise, J., Barron, A. G. de, Splendiani, A., Balali-Mood, B., Vasant, D., Little, E., Mellino, G., Harrow, I., Smith, I., Taubert, J., van Bochove, K., Romacker, M., Walgemoed, P., Jimenez, R. C., Winnenburg, R., Plasterer, T., Gupta, V. & Hedley, V. (2019). Implementation and Relevance of FAIR Data Principles in Biopharmaceutical R&D. Drug Discovery Today, 24(4), 933–938. https://doi.org/10.1016/j.drudis.2019.01.008

Wu, M., Psomopoulos, F., Khalsa, S. J. & Waard, A. de (2019). Data Discovery Paradigms: User Requirements and Recommendations for Data Repositories. Data Science Journal, 18(1), 3. https://doi.org/10.5334/dsj-2019-003

Yuan, W. (2020). Fair Data Transactions Across Private Databases. IEEE Access, 8, 53720–53732. https://doi.org/10.1109/ACCESS.2020.2979813

Zhao, Y., Yu, Y., Li, Y., Han, G. & Du, X. (2019). Machine Learning Based Privacy-Preserving Fair Data Trading in Big Data Market. Information Sciences, 478, 449–460. https://doi.org/10.1016/j.ins.2018.11.028


Online-Quellen

BMBF - Digitale Zukunft: Mit GO FAIR auf dem Weg zur europäischen Wissenschaftscloud. (2019). https://www.bildung-forschung.digital/de/mit-go-fair-auf-dem-weg-zur-europaeischen-wissenschaftscloud-2173.html

Forschungsdaten.org: FAIR Data Principles. (26. Mai 2020). https://www.forschungsdaten.org/index.php/FAIR_data_principles

GO FAIR: FAIR Principles. (18. August 2020). https://www.go-fair.org/fair-principles/

TIB-Blog: Die FAIR Data Prinzipien für Forschungsdaten. (2017). https://blogs.tib.eu/wp/tib/2017/09/12/die-fair-data-prinzipien-fuer-forschungsdaten/

Zuletzt geändert: Dienstag, 29. Juni 2021, 14:36