and 3 more

TU Delft 30/11/2017 1. TU Delft university presentation Larger tech university in Netherlands (founded 1842)- more than 20000 students, 8 faculties , >5000 staff.Open science as one of the main stakes for the old and also for the new rector Curiosity and openness as anchor value; being confident and renewing as aspiration value; foundation value is connecting -> promise let knowledge flow freely ("freedom to excel")2020 milestones: relevant scientific information should be findable, searchable, reusable, divisible. -> 46% publications OA 4 main areas of work: discovery and deliver; data at work (they started 7-8 years ago); publication and impact (negotiations with publishers in order to complain with OA; contracts with OA publishers; OA fund); library environment (individual and group working spaces). -> there is also the R&D group for innovating and future-proof services. Organisation: research services; education services; resources; overarching (R&D, liaison & policy support, communication). 124 people in the library. (92 EPT)Open research, education, innovation, campus -> values for 2018-2024 (Open Science PhD training @Delft) 2. TU Delft Library collection Content and licensing not managed by the same people. Barely buy paper books. In 2003 change of acquisition policy; 1.000.000 paper books in the basement; PDA from 2010 (-> Mediate PDA, with motivation from the reader, and someone in the library who check if the ebook is already accessible via another providers; there is also a limitation on price - no more than 200 USD/book). Missions -> support university education and research programs AND anticipate on new multidisciplinary research fields. Journals in the framework of Consortium deals. Impossible to have more tailored (and smaller) collections (even if it is done with the other TU). Focus only on the requests/needs of users (not on turnaways :-)). System: via OCLCMain issues: budget cuts: split between core collection and additional collection -> difference in the way of financing publishers policy (see above) less HR for collection tasks (no subject librarians): no direct links with faculties anymore. Twice a year: meeting with faculties to collect wishes and needs (for books acquisition only: PDA/Proquest; Evidence Based acquisition/Elsevier). insights in usage: need for better numbers (which faculty is using what -> this is the main info they would like to have). Implementation of EZ Proxy (can create more problems compared to IP range). Through ezPAARSE they can monitor and identify major user groups. 3. TU Delft Research services (35 people)  Strategic framework 2018-2014 (to be published in November :-)) for TU Delft "Impact for a better society" (slogan of the university). The present slogan in "Freedom to excel". Big focus on the main world wide issues (energy, resources, etc.). Open science as systemic change - all is about sharing! Enhance scientific research: - Enlarge dissemination; - open FAIR data- open courses- open software- Stimulate cooperation (instead of competition; new rewarding system; new metrics); - Work on citizen participation (scholarly comm & involving people in science). The service offers full support to the research cycle. Scientific information : from subscriptions to OA; from just in case to just in time; for ownership to providing access. Data sharing and archiving: 4TU.Centre for RD; Digital lab notebook (put everything in one system... ongoing, not easy work); Open software (less published; problem of recognition)Publishing support: academic visibility (all TU Delft outputs are made available - at least metadata -  with institutional /faculty brand); TU Delft Open -> proper publisher (already published journals, mainly architecture); research intelligence (new ways of evaluating research).  Governance of scientific process -> it is a need because: - they had issues on scientific integrity in the Netherlands - Archiving research and education - Repository, data archive, lab notebooks. [Labservant (?) -> chemistry domain -> CHECK! ]4. Open Access promotion and financing in Netherlands Promotion kit -> How to guide; Making an impact with OS (-> course for PhD https://www.tudelft.nl/onderwijs/opleidingen/phd/doctoral-education-programme-de/training-programme/r1a3-making-an-impact-with-open-science/); POLICY ON OA; National OA monitor (now mature). TU Delft on OA publishing pretty easy -> as TU Delft author, you have to publish at least the final accepted version of a peer-reviewed article with required metadata in the TU Delft Institutional Repository. Most common question: how to finance OA? At the national level -> OFFSET AGREEMENTS WITH PUBLISHERS. There around 8000 journal with OA discount. Schéma in the library catalogue (library.wur.nl) for journals, with info related to the journal (APC Discount, Green OA - info from Sherpa/Romeo - , impact, recent articles). Pre-paid models (proper to TUDelft): Copernicus, MDPI, PLOS, IOS Press, Frontiers, PeerJ. Classic TU Delft OA fund (starting in 2008) - Individual financial support: around 380 sponsored publications (increase of requests for OA ebooks). Repositories @TU Delft:Research repository -> core one Education repository Cultural heritage repository Different repositories because of different purposes, and metadata, and different (or no) implication of publishers. OA TU Delft publications: 2013 / 15%; 2015: 30%; 2016 / 44%. Ambition for 2018 -> 60%. Copyright Information Point TU Delft, with a dedicated website. -> list of useful links at the end of presentation (if shared). 5. Research analytics toolbox Why: gain insights into the positioning of a research filed, identify patterns and trends within research fields, ... -> research analytics in Delft introduces researchers and faculties with a toolbox (data sources and powerful and easy to use analysis and visualization tools). Need for a better use of data science tools in order to provide appropriate responses to these questions (ex.: datasets available for biblio metric; position of my group in relation to the competitors; etc.). 3 steps in the process: data collection, analysis, communication. Offer these steps in an integrated manner: AIDA (Automatic IDentification of reseArch trends), offering the toolbox out there, and the library provides the basics to let the researchers DIY. - Data collection: from where? WOS, Scopus, Pure, Almetrics, CWTS - Data analysis: some of the databases have already analytical features, but also excel is pretty powerful. Some of these tools need extra methodologies or TDM. - Communication: the main purpose of the rest of the work (Aida.tudelft.nl) Almetrics project @ TUDelft -> this toolbox (and related tools and databases) lay on the traditional citation system. To go further in the path of Open Science, they are running a test/exercise with Altmetrics. Choice of 900 doi, and analysis creating a link between citations and altmetrics score. TU Delft library provides research analytics support (check library website) for this toolbox to Individual researchers, faculties, policy makers. (Almetrics.com -> check). 6. Data stewardship (slides on the blog) - Policy framework : develop a system where every faculty could develop its own policies (DMP, PhD training, Obligatory deposit), in a general policy framework. - Culture of data stewardship: What issues? How to build a responsible RDM? Responding to strategic drivers from funders & recognition and rewards for OS Ensuring transparency and reproducibility Not losing data What actions? Data stewardship project embedded in the faculties (first contact point in each faculty) and extra support from data officers in the library. (1 repr per Faculty (0.5 EPT))Role of data stewards -> Assisting in the planning collection, management and publication of data in new and ongoing projects, Help writing DMP Outreach and advocacy Understanding trends Running faculty specific training Providing advice on specific issues (mainly publication) Quantitative and qualitative metrics to assess the success of data stewardship Direct link with senior management in the faculty Infrastructure: 4TU.Research Data -> data archive provision to researchers (guaranteed for 15 years). Future plans: API to allow programmatic access to archive, greater functionality for sharing data during the project; different publishing options; ongoing work on technical infrastructures. Reviewing the metadata (not the data!) of each dataset (title, link to the article, ORCID; etc). If there is no readme file, the dataset is rejected (methodology, acronyms, ...). The back office cannot check the reliability of data itself. The time spent is 1 hour per dataset (more or less 150 dataset/year). Ongoing project to make data deposition mandatory for PhD at the end of their cursus. Process of outsourcing the infrastructure. Too expensive to maintain the current one (HR and costs only to maintain the current structure, not to improve it/make it evolve). -> Figshare or Mendeley Data (TUDelft in the middle of the tender procurement to choose). Embedded data stewards, systematic and discipline-base training, ... Rotterdam - Erasmus University 01/12/2017 1. Strategy University Library(Gert Geris Deputy director, research intelligence, research outputs )University: 28000 students, 3000 staff, social sciences, biomedical sciences, humanities. Budget 588M €Library: 900 places, 75 employees (62 FTE), 900'000 volumes -> dept.: Academic services (supporting education and research), Library learning center, Information provisioning. Mission: support to creations and dissemination of knowledge. Promise: content manager of the UniversityBridge between customers and library.Creation of new services: - creation together with customers, but still gap or mis-knowledge of them. Need for a new way of building new services. - Research intelligence RESEARCH SERVICES: Grant support Research Intelligence (data scientists , bibliometricians, ...) Legal RDM Valorisation -> Build communities around these axes, and build within these communities services and communication. IT and other support dept are also involved. Other university library services: information literacy, data service center, research evaluation assessment service. Services are put in several communities (among the ones before mentioned). Research intelligence community : creation of the community -> by invitation (?) Missions: Monitor and manage research performance (quality, relevance, strategy, visibility,...) Support international collaboration networks Improve funding win-rate Monitoring global research trends (multidisciplinaire developments and emerging topics) Responsible metrics (analysis reports and support for research quality assurance Action to enhance dissemination Further developments : funding intelligence; RD intelligence (data citations, mapping the use of RD through research output analysis) Many tools used for that (data collection and analysis tools). Last summer a Research Intelligence network Netherlands has been established (CHECK!!!). LDE research intelligence initiative (Leiden, Delft, Erasmus). 2018 goals: identity management, research evaluation; training in use of Scival, InCites, Altmetrics; support in publishing OA; development of a predictive modeling service. 2. ACADEMIC SERVICES departmentResearch and education support (also tailor made), Front office, Liaison, RDM, ... Both "traditional" and "new/research oriented" ones (OA, OS; RDM, Research intelligence, copyright, Privacy law); training in academic skills. Specialists: faculty liaison, information specialist, data librarians, data intermediary, web coordinator, specialist licences and OA. Focus 2018: digitalization, intensify cooperation with faculties. Strong move to digital content in 2015 (250.000 less books - out of collections). 5-years-strategy: merging of different libraries, and working processes accordingly. National consortium -> UKB, 13 libraries, for negotiations (from 55 to 75 licences in 4 years). Transition to Worldshare platform (check SURFmarket). Modification in the budget allocation, loans, usage of resources (printed and paper) -> need for a shift on the hired people (new skills and competencies needed). For electronic resources, different models are used according to fit the services (Pick & Choose, EBS; PDA; Short term loans). Enhanced used of statistics. Pilot on e-studybooks. 2018: only e-acquisitions, unless you have a very good excuse :-) 3. RDM, FAIR and Open science Central policy starting with the FAIR principles and Baseline protocol (main elements to be put in RDM responsible reflection -> 15 points). Implementation in faculties of the protocol based on FAIR. Data services -> information provision, legal support, practical advice for storage, sharing and privacy, support for DMP, and data paragraphs in grant and research proposals, Erasmus Data Service Centre (EDSC -> best practice example on how to organize RD services) EDSC: largest portfolio of economic and financial databases, access to on-site DB, guidance and support for DB (based on a voucher system), workshops for students, manual & FAQs, facilitation of student events. 2018-2021 strategy: providing access to more DB (TDM); subject as a base to organize a workshop: boost and more explicit role in the research data infrastructure (help more in the active phase of research); ... Open Science -> data education standards access. How to get people on board? How to transform principles in real practice? OS priorities: - providing access to more and different content (new databases, TDM, GIS analysis; collect and stimulate the use of Open Data). (Fair _> accessible, interoperable; OS: empowerment) - Focus on subject oriented support and development of EDSC knowledge center - Boosting the EUR research data infrastructure (lead the IRODS workgroup in the RDM community (FAIR: findable and accessible; OS: collaboration transparency and sharing) - Expansion of EDSC services (EDSC should become data collector and producer; draw up a service for TDM; support for the use and analysis of large datasets with google big query, and google cloud platform). FAIR-> interoperable and reusable; OS: collaboration and empowerment - Intensify internal and external cooperation: stronger collaboration with Erasmus Data Science community ; participate in blockchain project (FAIR: I, R; OS: collaboration and empowerment).