FAIR and open biodiversity collection data management
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The document discusses open science as a movement aimed at increasing accessibility to scientific research, data, and methodologies, emphasizing the need for greater transparency and reproducibility in the scientific community. It highlights the evolving role of natural history museums and data repositories in this context, advocating for open data policies and fair data management practices. Furthermore, it addresses the challenges of scientific irreproducibility and encourages a shift toward sharing data and methodologies to foster trust and collaboration in research.
FAIR and open biodiversity collection data management
- 1. Photo from Smithsonian Museum of Natural History Seminar at Sundvolden, 5th March 2020
- 2. WHAT IS OPEN SCIENCE? “Open science is the movement to make scientific research (including publications, data, physical samples, and software) and its dissemination accessible to all levels of an inquiring society, amateur or professional” https://en.wikipedia.org/wiki/Open_science Woelfle M, Olliaro,P, Todd MH (2011) Open science is a research accelerator. doi:10.1038/nchem.1149
- 3. Open Access (OA): Research results (often meaning research articles) distributed online and free of costs or other barriers. Open Science: Researchers to share their methods, materials, computer code, algorithms, and research data. Open Data: is freely available to everyone to use and re-publish as they wish, without restrictions from copyright, patents or other mechanisms of control.
- 4. WHAT IS OPEN SCIENCE? Open Science can be seen as a continuation of, rather than a revolution in, practices begun in the 17th century with the advent of the academic journal cf. Wikipedia; David 2004 … and arguably also a continuation of the practice of natural history collections. David, PA (2004) Understanding the emergence of 'open science' institutions: Functionalist economics in historical context. doi:10.1093/icc/dth023
- 6. WHY APPROACH OPEN SCIENCE IN MUSEUMS?
- 7. WHY APPROACH OPEN SCIENCE IN MUSEUMS? v We are in the middle of an ongoing paradigm shift in scientific practice (and impact metrics). v The open science wave is moving fast! v Natural History Museums will need to develop different approaches, than they needed in the past – to remain relevant. v Society is quickly gaining Big Data maturity and will expect new services from museum collections.
- 8. The total number of specimens in natural history collecZons worldwide is esZmated to 1.2 - 3 billion. (Ariño 2010; Duckworth et al. 1993) GBIF publishes 1,4 billion records – including 168 million specimens 5% to 10% coverage? Photo: Botany Collection, Algae, Smithsonian National Museum of Natural History Museum, by Chip Clark.
- 9. DIGITIZED SPECIMENS AT UIO NHM OSLO (47%)
- 10. The Government of Norway has decided that the public sector shall digiZze Norway to follow the ambition of EU on full open access to publicly funded research by 2020. Research data must be as open as possible and as closed as necessary. Research data should be managed and organized so that the values in the data can be utilized to the best possible extent. Ministry of Education and Research, 2017 digitaliseringsminister Astrup Helleland
- 11. Established 1st January 2018, after combining BIBSYS, Ceres, and parts of Uninett. Mission statement: ○ An innovative driver for digitisation. ○ Utilize new technology to improve efficiency, improve quality, and ensure access to knowledge. Direktoratet for IKT og fellestjenester i høyere utdanning og forskning
- 12. The European Open Science Cloud will uncover a “hidden treasure and untapped opportunities”. A multi-billion euro project to transform research and add value to vast stores of unused data. Research data free to use for science including non-EU researchers. EU President Ursula von der Leyen, in Davos February 2020
- 13. The European Open Science Cloud – EOSC – a virtual environment for services for data storage, data management, data analysis, and reuse of research data across countries and scientific diciplines.
- 14. REPRODUCIBILITY CRISIS Scientific irreproducibility the inability to repeat others' experiments and reach the same conclusion (Nature 2016) Baker (2016) 1,500 scienZsts lif the lid on reproducibility. Nature doi:10.1038/533452a
- 15. "Scientific irreproducibility — the inability to repeat others' experiments and reach the same conclusion — is a growing concern”. Baker (2016) Nature doi:10.1038/533452a Open Science solution: researchers to share their methods, data, computer code and results in central data repositories. Note that we also need herbarium specimen and bio-repositories (eg. museums).
- 16. WILL ANYBODY TRUST CLOSED SCIENCE AGAIN? Recent studies indicates that p-hacking is a significant problem – sometimes without the scientist even being aware of doing so. p-hacking, occurs when researchers collect or select data or statistical analyses until nonsignificant results become significant. Pre-registered (open) data & material samples provides an insurance against suspicion of data dredging (and plain data falsification). Ioannidis (2005) Why Most Published Research Findings Are False. PLoS Med. doi:10.1371/journal.pmed.0020124. Head et al. (2015) The Extent and Consequences of P-Hacking in Science. PLoS Biol. doi:10.1371/journal.pbio.1002106
- 18. CREDIT FOR DATA REUSE To incentivize the sharing of useful data, the scientific enterprise needs a well- defined system that links individuals with reuse of data sets they generate Pierce et al. Credit data generators for data reuse, Nature 6 June 2019
- 19. DATA CITATION AS A NEW CURRENCY OF SCIENCE ● Peer-reviewed scholarly papers in high impact journals maintain considerable weight for impact metrics. ● A movement is under way to build similar status for open data, open metadata, open material samples, and other open scientific research products…
- 20. DATA CITATION PRINCIPLES 1. Data to be legitimate citable products of research. 2. Data citations giving scholarly credit and attribution. 3. In scholarly literature, whenever claims are based on data, data should always be cited. 4. Persistent method for identification of data, that is machine actionable, globally unique, universal. 5. Data citation facilitate access to data or at least to metadata. 6. Unique identifiers that persist even beyond the lifespan of the data. 7. Data citation identify and access the specific data that support verification of the claim (provenance, time-slice, version). 8. Flexible, but attention to interoperability of practices across communities. Data Citation Synthesis Group: Joint Declaration of Data Citation Principles. Martone M. (ed.) San Diego CA: FORCE11; 2014
- 21. OPEN RESEARCH DATA POLICIES ● Scientific journals is starting to provide guidelines for availability of research data to accompany published research papers. ● GBIF is here recommended as a data repository for biology. ● Museum collections could provide a similar function for open availability to biological material samples… http://www.springernature.com/gp/group/data-policy/policy-types
- 22. Barend Mons (2020) Invest 5% of research funds in ensuring data are reusable. Nature 578: 491 doi:10.1038/d41586-020-00505-7 27 February 2020
- 23. OPEN RESEARCH DATAThe Research Council of Norway expects all research data from projects funded by the Research Council to be made freely available as open data. (For some situaGons there can be valid and jusGfied reasons for excepGons). (2014, updated 2017, 2020)
- 24. It is irresponsible to support research but not data stewardship. Huge sums of taxpayer funds go to waste because such data cannot be reused. On average, 5% of overall research costs should go towards data stewardship. If data are treated properly, researchers will have significantly more time to do research. INVEST 5% OF RESEARCH FUNDS IN ENSURING DATA ARE REUSABLE Barend Mons, Nature 578: 491, 27 February 2020 Barend Mons co-leads GO FAIR and is the co-author of the FAIR principles (2016)
- 25. Promotes maximum (re)use of research data Researchers need to do more than simply post their data on the web for it to be useful Wilkinson et al. (2016) The FAIR guiding principles for data management and stewardship. doi:10.1038/sdata.2016.18
- 26. GBIF | CERTIFIED FAIR DATA Global Biodiversity Information Facility (GBIF) provides certified FAIR data sharing for all biological datasets Distributed System of Scientific Collections (DiSSCo) will implement FAIR data principles for natural history collections
- 27. GBIF enables free & open access to biodiversity data online We are an international government-initiated and -funded initiative focused on making biodiversity data available to all and anyone, for scientific research, conservation and sustainable development
- 28. Map updated 10th March 2019 M ostdataarefrom morerecentdates
- 29. More than 700 – about 2 papers a day Peer-reviewed publications using GBIF-mediated data
- 30. Total # of peer-reviewed papers by country 1 United States 70 2 United Kingdom 35 3 China 31 4 Brazil 28 5 Spain 24 6 Mexico 23 7 Canada 21 8 Germany 18 9 Italy 15 10 Australia 14 19 Sweden 9 … Norway 8 PEER-REVIEWED USES BY COUNTRY AND REGION STATUS JAN-FEB 2020 – TWO MONTHS (281 CITATIONS)
- 31. Open science provides possibilities for new & curiosity-driven research Open science Traditional science Modern museums
- 32. FAIR and open biodiversity collecFon data management 5th March 2020, NHMO Science seminar, Sundvolden