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Tibor Koltay, Eszterházy Károly University: Beyond Literacies: The evolving landscape of library support to Research 2.0

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V Międzynarodowa Konferencja Naukowa Nauka o informacji (informacja naukowa) w okresie zmian Innowacyjne usługi informacyjne. Wydział Dziennikarstwa, Informacji i Bibliologii Katedra Informatologii, Uniwersytet Warszawski, Warszawa, 15 – 16 maja 2017

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Tibor Koltay, Eszterházy Károly University: Beyond Literacies: The evolving landscape of library support to Research 2.0

  1. 1. Beyond literacies: The evolving landscape of library support to Research 2.0
  2. 2. Tibor KOLTAY Department of Information and Communication Eszterházy Károly University, Hungary koltay.tibor@uni-eszterhazy.hu 2
  3. 3. DISPENSARIES OF BOOKS AND ARTICLES? • “Libraries focus mainly on issues regarding the output of scholarly communication“ = collecting journals, monographs and other documents • They should focus more on researchers’ changing information behaviour. 3
  4. 4. ENABLING FACTORS • Widespread availability and use of ICTs, • Technological innovations: by the Web 2.0 (social media) • Abundance and relatively easy access to research data 4
  5. 5. RESEARCH 2.0 • Science 2.0, eScience, digital scholarship 5
  6. 6. RESEARCH 2.0 • Data-intensive research • Open Science = Open Data = Open Access to scholarly publications • Use of social media 6
  7. 7. WHERE IS RESEARCH 2.0? • In the natural sciences, • the social sciences, • the arts and humanities • In different countries to a varied degree 7
  8. 8. • You my feel that Research 2.0 is not yet here. • It is there = somewhere in a few countries in several environments 8
  9. 9. ISSUES AND ACTIVITIES • Research data services (RDS) • Data literacy education • Raising awareness on different issues • Supporting individual teaching staff members • Awareness-raising • Changing roles for/of the information professional 9
  10. 10. RESEARCH DATA SERVICES • An overall service framework • that is related to these processes and should be provided by academic libraries. 10
  11. 11. RDS Include • Research data management (RDM), • Data curation (not clearly differentiated from RDM), • Data stewardship, • Data governance. 11
  12. 12. RESEARCH DATA MANAGEMENT • A set of general activities not specifically attached to the library, but potentially performed by it. • Informational services • Technical services 12
  13. 13. THE RDM LIFECICLE 13
  14. 14. RDM IN SHORT Caring for research data, Facilitating access to it, Preserving and adding value to it 14
  15. 15. INFORMATIONAL SERVICES • Consulting with faculty, staff, or students on data management plans and metadata standards; • Reference support for finding and citing data sets; • Providing web guides and finding aids for data or data sets. 15
  16. 16. DATA REFERENCE INTERVIEWS • Are rooted in traditional librarianship. = Pointing towards some useful starting points → Finding the perfect source • More complicated and consist of more questions than the traditional ones. 16
  17. 17. TECHNICAL SERVICES • Providing technical support for data repositories, • Preparing data sets for a repository 17
  18. 18. DATA GOVERNANCE • Usually a subject of interest for the business sector. 18
  19. 19. DATA GOVERNANCE REGULATES… • Who can take what actions, when and under what circumstances, using what methods? = Decision rights and accountabilities, based on agreed-upon models, • Deals with availability, access, provenance, meaning and trustworthiness. = data quality 19
  20. 20. • Trust, e.g. the reputation of those responsible for the creation of the data • Authenticity • Accessibility 20
  21. 21. 21
  22. 22. DATA LITERACY • A specific skill set and knowledge base, • Empowers individuals to transform data into information and into actionable knowledge • by enabling them to access, interpret, critically assess, manage, and ethically use data. • Should incorporate the social and technical aspects of data. 22
  23. 23. DATA LITERACY COMPETENCIES • Knowing how to select and synthesize data and combine them with other information sources and prior knowledge. • Identifying the context in which data is produced and reused; • Recognizing source data value, types and formats; • Determining when data is needed; • Accessing data sources appropriate to the information needed; • Critically assessing data and their sources; 23
  24. 24. • Determining and using suitable research methods; • Handling and analysing data; • Presenting quantitative information; • Applying results to learning, decision making or problem-solving; • Planning, organizing and assessing ourselves throughout the process. 24
  25. 25. • Looks like something familiar? 25
  26. 26. • Just like information literacy 26
  27. 27. DATA LITERACY AND THE LITERACIES 27
  28. 28. 28
  29. 29. DATA LITERACY EDUCATION • Data quality, • data citation, • and metadata are foundational. 29
  30. 30. DATA CITATION • Identification, retrieval, replication, and verification of data • It can motivate researchers to publish data.  Reward and acknowledgment 30
  31. 31. METADATA • Creating metadata for data sets that supplements the provision of “traditional” metadata  • Libraries may Occupy a niche in the support chain 31
  32. 32. SUPPORTING INDIVIDUAL FACULTY MEMBERS Make clear • What is the perception of librarians about their own role in relation to the research activities of faculty and what do they want to achieve? • What is the perception of faculty members about the supporting role of librarians in their research? 32
  33. 33. FORMS OF SUPPORT • Providing informal alerting services • Purchasing requested resources • Answering in-depth reference questions • Creating visual representations of data • Consulting about searching 33
  34. 34. RAISING AWARENESS • Non-traditional activity = Not offered directly by the libraries themselves • Social media tools • Open access to scientific publications • Open data • Alternative metrics of scientific output 34
  35. 35. ACADEMIC SOCIAL MEDIA TOOLS • Restricted use ↔ • Raise awareness to tools 35
  36. 36. 3636 36
  37. 37. • Researchers must publish their work in in prestigious, peer-reviewed journals (books).  Social media cannot serve as a wholesale replacement for those channels. 37
  38. 38. RESEARCHERS • Often reluctant to share professional information with a wide and uncontrolled audience. • Likely to accept new methods if they improve the research outcomes • and do not threaten their reputation. 38
  39. 39. OPEN ACCESS • Diamond, Gold and the Green routes • Article processing charges→ • Predatory publishers ↔ • White list Directory of Open Access Journals (DOAJ) 39
  40. 40. ALTERNATIVE METRICS 40
  41. 41. • Alternative metrics are complementary to traditional measures, • represent different aspects and disciplines • Not familiar to most researchers; • The related beliefs and norms of professional communities may change, • though change is usually slow. 41
  42. 42. NEW ROLE MODELS FOR ACADEMIC LIBRARIANS 42
  43. 43. 43
  44. 44. • Librarians are not data scientists. ↔ • There are intersections between them in data management and in the attention to data quality. 44
  45. 45. • Being specialised in examining pattern and syntax and using quantitative methodology, • OR caring for meaning, semantics and using qualitative methods • Do not exclude each other. 45
  46. 46. LERU • League of European Universities • Academic libraries can provide help in increasing the visibility of research data, • Well placed to advocate best practices in data management and data citation • Supporting RDM is a new role for them. • RDM requires cooperation between librarians and researchers. 46
  47. 47. THE MAIN AIM • Minimize the time that researchers have to spend on technical and administrative processes. 47
  48. 48. RECOMMENDATIONS • Association of European Research Libraries (LIBER) = Ten recommendations for libraries to get started with research data management (2012) • There is no need to start with all recommendations • Learn from others, adopt best practices. 48
  49. 49. • Offer research data management support, including data management plans for grant applications • Engage in the development of metadata and data standards and provide metadata services for research data. • Create Data Librarian posts and develop professional staff skills for data librarianship. • Liaise and partner with researchers, research groups, data archives and data centres. 49
  50. 50. THIS PAPER WAS SUPPORTED by the EFOP-3.6.1-16-2016-00001 project “Complex Development of Research Capacities and Services at Eszterházy Károly University"
  51. 51. Thank you for your attention. 51

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