Libraries Advancing Open Science Agenda
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LIBER is a pan-European organization representing over 420 research libraries. It advocates for open science policies to increase transparency, quality, and innovation. Open science involves making research outputs like publications, data, and communication freely available and reusable. LIBER supports related EU initiatives and helps libraries develop services for open science, such as research data management. It also lobbies policymakers on issues like copyright reform to better support open practices like text and data mining. LIBER works with other library organizations internationally to advance a common vision of open access to information.
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Libraries Advancing Open Science Agenda
- 1. Libraries Enabling Open Science: LIBER Strategy & Advocacy Susan Reilly Executive Director, LIBER, the Association of European Research Libraries LAI/CILIP Ireland, Killarney, 14 Apr @skreilly
- 2. Overview Introduction to LIBER The Open Science Agenda in Europe LIBER Advocacy The Collective Role of International Library Organisations
- 3. What is LIBER? A pan-European membership organisation representing 420+ research libraries from across Europe Mission to create an information infrastructure that enables research in LIBER institutions to be world class
- 5. Competitiveness Council of Europe European Commission • H2020 Open Data Pilot • Digital Single Market • Open Science Cloud • Development of open science agenda • Importance of skills, infra The Digital Single Market: Open Science in Europe European Parliament • Copyright legislation • H2020 funding
- 6. Science in Transition: from Science 2.0 to Open Science EU consultation on Science 2.0 (July- September 2014) 498 responses and 27 position statements 43% of respondents chose “Open Science” as their preferred term out of 6 terms
- 7. Drivers for Open Science
- 8. Areas for Policy Intervention Open Access & Copyright Citizen Science Researchers’ Careers Peer Review & Research Evaluation New Metrics Other: Funding, Skills, Infrastructure
- 9. 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
- 10. 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=269
- 11. 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 notebooks Collaboration Coyright & licencing Policy Advocacy & training Alternative Metrics Open data Open source
- 12. From Gate Keeper to Embedded Librarian Findable + Accessible + Usable +Reusable = Sustainable Information Access
- 13. Fake data!
- 14. The Commons Are Forever (Newcastle)
- 16. 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
- 17. Mobilising our Libraries: RDM
- 18. Making the Case to Policy Makers: Netherlands EU Presidency Open Science Conference Amsterdam, 4/5 April 2016
- 19. Mobilising the Community: Copyright Recognition that copyright needs to be modernised to support Open Science and the Digital Single Market European Commission to publish proposals for copyright reform in October 2016 TDM Cross Border
- 20. Text & Data Mining is the future “Text and data mining (TDM) is the process of deriving information from machine-read material. It works by copying large quantities of material, extracting the data, and recombining it to identify patterns.” JISC
- 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
- 24. 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/
- 25. 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
- 26. 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
- 27. The Collective Role of International Library Organisations “The library is a growing organism” (Ranganathan, 1931) Common vision Best practice Capacity building Share infrastructure High level representation
- 28. The Collective Role of International Library Organisations Partner with other stakeholders Represent our users Make the case for access to information Everyone has the right to freedom of opinion and expression; this right includes freedom to hold opinions without interference and to seek, receive and impart information and ideas through any media and regardless of frontiers. Article 19, Universal Declaration of Human Rights
Editor's Notes
- LIBER was one of those respondents. In fact we released a statement recognising the importance of open science and calling on the Commission to support 5 key enablers of open science: policy and leadership (roadmaps for open data, coordination of clear policy), advocacy and recognition (promoting open science and recognising contributions, law reform to address contradiction in copyright law, infrastructure (particularly interoperability), roles and skills (training, education, involvement of stakeholders).
- It should be an ecosystem of sharing and collaboration, of re use and redistribution. Open Science is difficult to define, but here is a definition from the FOSTER project: a project on open science training. Shared as early as possible Open unless…
- Another way to look at the problem of defining open science is to look at what it’s goals are. I particularly like this set of goals outlined by Dan Gezelter from OpenScience.org. The only thing I would add is an ‘open’before web-based tools.
- So we are moving from a black box environment to a landscape of open research and scholarship. Maybe now you can understand what a challenge Eva Mendez presented me with when she invited me to speak about open science. But I will focus, in this talk primarily on data and just touch on a few other topics. I think the important thing to note here is that instead of having an end point (the publication) open science turns research back into an ongoing dialogue, which is its natural state and moves it away from the artificial construct of publication as an end point
- As I said, representing libraries and being a librarian myself I have a bias in that I believe that libraries have a key role in enabling open science, starting with advocacy and moving towards supporting practice, developing infra and standards, and providing access to tools. I don’t see how any other stakeholder can fill this space in a coherent way
- And sligthly different, but just as interting for this crowd: just this week, we co-organised four Open science cafes where we discussed all kinds of aspects of open science in an open discussion: one of the discussion statements was: “libraries should spend money on preserving software in order to keep data available for re-use”
- It will foster best practices of global data findability and accessibility (FAIR data), help researchers get their data skills recognised and rewarded (careers, altmetrics); help address issues of access and copyright (IPR) and data subject privacy; allow easier replicability of results and limit data wastage e.g. of clinical trial data (research integrity); contribute to clarification of the funding model for data generation and preservation, reducing rent-seeking and priming the market for innovative research services e.g. advanced TDM (new business models).
- Text and data mining (TDM) is the process of deriving information from machine-read material. It works by copying large quantities of material, extracting the data, and recombining it to identify patterns. TDM is essentially another method of reading, done by the computer rather than the human eye. It is a natural next step for the research process, as more and more content is electronic. For libraries what this means is that researchers are able to extract more value from our vast collections- born digital and digitised. I’d like to show you some examples of the added value of TDM.
- Physicist T.C. Mendenhall hired 2 women to count the length of words in Shakepeares works. Word length frequency curve remains consistent- way to ascertain authenticity. Unlike most English authors he used more 4 letter words than 3 letter words. No correlation to Bacon but (as was discovered years later) was as similar to Christopher Marlowe (another Elizabethan playwrite and poet) as he was to himself
- The free flow of information and ideas is an essential human right4. It is a catalyst for the production of human knowledge, which underpins welfare and prosperity. Societies around the world have chosen to protect certain limited rights in intellectual property as incentives both to innovation and the dissemination of knowledge. Intellectual property law was never intended to cover facts, ideas and pure data. However the modern application of intellectual property law is increasingly becoming an obstacle to knowledge creation and dissemination that use even these most simple building blocks of knowledge. In some countries, copyright law5 in particular has been interpreted to restrict the ability to apply computer reading and analysis to otherwise legally-available content. Other legislative frameworks such as patent law and database law may have a similar impact. When intellectual property law allows content to be read and analysed manually by humans but not by their machines, it has failed its original purposes.
- The free flow of information and ideas is an essential human right4. It is a catalyst for the production of human knowledge, which underpins welfare and prosperity. Societies around the world have chosen to protect certain limited rights in intellectual property as incentives both to innovation and the dissemination of knowledge. Intellectual property law was never intended to cover facts, ideas and pure data. However the modern application of intellectual property law is increasingly becoming an obstacle to knowledge creation and dissemination that use even these most simple building blocks of knowledge. In some countries, copyright law5 in particular has been interpreted to restrict the ability to apply computer reading and analysis to otherwise legally-available content. Other legislative frameworks such as patent law and database law may have a similar impact. When intellectual property law allows content to be read and analysed manually by humans but not by their machines, it has failed its original purposes.