1. Open Science is More than Open Access, but what is it? Susan Reilly @skreilly Executive Director Brussels, October 2015

2. I’ll be talking about… LIBER & Open Science Definition of Open Science Building blocks of Open Science What’s it all for? Knowledge Discovery

3. LIBER: reinventing the library of the future Largest network of European research libraries: 410 in over 40 countries Mission: “To provide an information infrastructure to enable research in LIBER institutions to be world class”

4. LIBER: Information Infrastructure for World Class Research? Collaborative 90% of research papers are collaborative International 40% of French & German research outputs a result of international collaboration Rate of citation grows as geographic extent of collaboration increases Interdisciplinary Foundation of frontiers research Data intensive supports interdisciplinary exploration … and open Higgs boson 2012 Journal Physics B paper: 6235 citations

5. Libraries enabling Open Science “We believe that the move towards openness will lead to increased transparency, better quality research, a higher level of citizen engagement, and will accelerate the pace of scientific discovery through the facilitation of data-driven innovation.” http://libereurope.eu/wp- content/uploads/2014/09/LIBER_Statement-on-open- science-final.pdf

6. Open Science Definition “The conduction of science in a way that others can collaborate and contribute, where research data, lab notes and other research processes are freely available, with terms that allow reuse, redistribution and reproduction of the research” https://www.fosteropenscience.eu/foster-taxonomy/open-science-definition

7. The problem with defining Open Science Means is often confused with the end Ultimate goal is to be a transient term i.e. Open Science = Science Aims to bring coherence and vision to a range of different open activities e.g. open access, open data, open software Key is changing practice and culture, which is different for every stakeholder Open Science = Diversity

8. Open Science Goals Transparency in experimental methodology, observation, and collection of data Public availability and reusability of scientific data Public accessibility and transparency of scientific communication Citizen engagement* Using web-based tools to facilitate scientific collaboration Dan Gezelter, http://www.openscience.org/blog/?p=269http://www.openscience.org/blog/?p=269 *EU

9. Work. Finish. Publish! (Faraday) Move away from a 300 year old model!

10. To an Open Science Landscape Open access publishing New forms of peer review Open infrastructure Research data management Open educational resources Massive Open Online Courses (MOOCs) Open science Collaboration Coyright & licencing Policy Advocacy & training Alternative Metrics Open data

11. Building block: open access “We write to communicate an untenable situation facing the Harvard Library. Many large journal publishers have made the scholarly communication environment fiscally unsustainable and academically restrictive. ” Harvard University Library, 2012 Moved beyond the tipping point: http://www.science- metrix.com/pdf/SM_EC_OA_Availability_2004- 2011.pdfhttp://www.science- metrix.com/pdf/SM_EC_OA_Availability_2004- 2011.pdf

12. It’s not just about the cost, it’s about the value… Accessible: make it available in accessible formats (XML) Findable: put it in open and sustainable infrastructure Reusable: attach clear permissions statements/licences

13. Building block: open data Need to release the value of data Benefits: Jobs (Copernicus= 50000 jobs) Research productivity (big bang) Help communities (flood hack) Cost of not sharing (bird flu) 1.7 million billion bytes of data every minute X 34

14. Data must be.. Open by default (G8,LERU) Usable by all Available Findable Interpretable Citable Curated/preserved

15. Building block: skills and training ReCODE Recommendation 10: Support the transition to open research data through curriculum-development and training.The transition to an open science paradigm where research data plays a significant role requires training and education for researchers and for data managers who support open science. Courses for getting researchers and data managers up-to date with current relevant issues are necessary, as well as the development of curricula that contribute towards the development of data science and information management as distinct and legitimate career paths. Need to embed training in post graduate education Invest in the development of the data professional Training provision as and when needed (importance of train the trainer) Training and support for new tools and methods

16. Building block: infrastructure International Open Interoperable Cross disciplinary Facilitate collaboration Store & Share Sync & Exchange Replicate Compute Find Content TDM tools Workflows Standards Interoperability

17. Building block: advocacy… Advocate for roadmaps and policies that promote open science at institutional and national level Advocate for changes in practice e.g. data citation, use of cc licences Promote your Open Science project Engage new audiences

18. and incentives Need to change system of incentives and assessment Move away from journal based metrics Consider value and impact of ALL research outputs (data, software…) Align assessment with institutional values Only a change of system of incentives will truly change practice and culture

19. Building block: policy and legislation Legal clarity Interoperabilty (WIPO solution?) Ensure researchers have right to secondary publication Standard open access licences CC-by and CC0/PD

20. Knowledge Discovery in the Digital Age Ultimate goal of text and data mining is to extract high level knowledge from low level data Allows analysis across disciplines “Undiscovered public knowledge” (Swanson) Identifies patterns in the data to produce new knowledge It’s not a new thing, it’s just digital information makes it a whole lot more powerful and relevant!

21. Human Computers (1901) http://marlowe-shakespeare.blogspot.nl/2009/02/on-mendenhall-and-compelling-evidence.html "This above all: to thine own self be true". 4 5 3 2 5 3 4 2 4

22. Use of words(2009) Marsden J, Budden D, Craig H, Moscato P (2013) Language Individuation and Marker Words: Shakespeare and His Maxwell's Demon. PLoS ONE 8(6): e66813. doi:10.1371/journal.pone.0066813

23. Cancer diagnosis(2013) http://theconversation.com/shakespeare-and-cancer-diagnoses-how-bard-can-it-be- 15381ata sets

24. Malhotra A, Younesi E, Gurulingappa H, Hofmann-Apitius M (2013) ‘HypothesisFinder:’ A Strategy for the Detection of Speculative Statements in Scientific Text. PLoS Comput Biol 9(7): e1003117. doi:10.1371/journal.pcbi.1003117

25. Copyright v TDM Because it involves the copying of content in order to convert into machine readable format TDM may infringe copyright European Database Directive prohibits copying of substantial parts of databases In US TDM is covered by fair use, other parts of the world have a specific exception e.g. Japan, UK https://www.flickr.com/photos/apelad/304195427/

26. The problem with licences Permission culture: Why relicence? Can’t licence everything! Not scalable or cost effective Will licence reflect how the researcher actually performs TDM? ME 442 Permission" by Nina Paley - http://mimiandeunice.com/2011/08/30/permission-2/. Licensed under Creative Commons Attribution-Share Alike 3.0 via Wikimedia Commons - http://commons.wikimedia.org/wiki/File:ME_442_Permission.png#mediaviewer/File:ME_442_Permission.png http://commons.wikimedia.org/wiki/File:ME_442_Permission.png#mediaviewer/File:ME_442_Permission.png

27. Elsevier TDM Policy Access through API only Text only- no images, tables Research must register details Click-through licence Terms can change any time Reproducibility of results

28. 1. INTELLECTUAL PROPERTY WAS NOT DESIGNED TO REGULATE THE FREE FLOW OF FACTS, DATA AND IDEAS, BUT HAS AS A KEY OBJECTIVE THE PROMOTION OF RESEARCH ACTIVITY

29. 2. PEOPLE SHOULD HAVE THE FREEDOM TO ANALYSE AND PURSUE INTELLECTUAL CURIOSITY WITHOUT FEAR OF MONITORING OR REPERCUSSIONS

30. 3. LICENSES AND CONTRACT TERMS SHOULD NOT RESTRICT INDIVIDUALS FROM USING FACTS, DATA AND IDEAS

31. 4. ETHICS AROUND THE USE OF CONTENT MINING TECHNIQUES WILL NEED TO CONTINUE TO EVOLVE IN RESPONSE TO CHANGING TECHNOLOGY

32. 5. INNOVATION AND COMMERCIAL RESEARCH BASED ON THE USE OF FACTS, DATA, AND IDEAS SHOULD NOT BE RESTRICTED BY INTELLECTUAL PROPERTY LAW

33. The Hague Declaration: http://thehaguedeclaration.com/the- hague-declaration-on-knowledge-discovery-in-the-digital-age/http://thehaguedeclaration.com/the- hague-declaration-on-knowledge-discovery-in-the-digital-age/ LERU Roadmap for Research Data http://www.leru.org/index.php/public/news/press-release-leru- roadmap-for-research-data/ http://www.leru.org/index.php/public/news/press-release-leru- roadmap-for-research-data/ EUDAT http://eudat.eu/http://eudat.eu/ Research Data Alliance https://rd-alliance.org/https://rd-alliance.org/ LIBER 10 Recommendation on Getting Started in RDM http://libereurope.eu/wp- content/uploads/The%20research%20data%20group%202012%20v7%2 0final.pdf http://libereurope.eu/wp- content/uploads/The%20research%20data%20group%202012%20v7%2 0final.pdf OpenAire https://www.openaire.eu/https://www.openaire.eu/ San Francisco Declaration http://www.ascb.org/dora-old/files/SFDeclarationFINAL.pdf