Have a personal or library account? Click to login
Supporting Data Discovery: Comparing Perspectives of Support Specialists and Researchers Cover

Supporting Data Discovery: Comparing Perspectives of Support Specialists and Researchers

Open Access
|Oct 2024

References

  1. 1Almeida, A.V. de, Borges, M.M. and Roque, L. (2017) ‘The European open science cloud: A new challenge for Europe’, in Proceedings of the 5th International Conference on Technological Ecosystems for Enhancing Multiculturality. New York, NY: Association for Computing Machinery, pp. 14. Available at: 10.1145/3144826.3145382
  2. 2Arora, S. and Chakravarty, R. (2021) ‘Making research data discoverable: an outreach activity of Datacite’, Library Philosophy and Practice (e-journal), p. 5199.
  3. 3Aryani, A. et al. (2018) ‘A research graph dataset for connecting research data repositories using RD-Switchboard’, Scientific Data, 5(1), p. 180099. Available at: 10.1038/sdata.2018.99
  4. 4Ashiq, M., Usmani, M.H. and Naeem, M. (2020) ‘A systematic literature review on research data management practices and services’, Global Knowledge, Memory and Communication, 71(8/9), pp. 649671. Available at: 10.1108/GKMC-07-2020-0103
  5. 5Bishop, B.W. et al. (2019) ‘Scientists’ data discovery and reuse behavior: (Meta)data fitness for use and the FAIR data principles’, Proceedings of the Association for Information Science and Technology, 56(1), pp. 2131. Available at: 10.1002/pra2.4
  6. 6Borgman, C.L., Scharnhorst, A. and Golshan, M.S. (2019) ‘Digital data archives as knowledge infrastructures: Mediating data sharing and reuse’, Journal of the Association for Information Science and Technology, 70(8), pp. 888904. Available at: 10.1002/asi.24172
  7. 7Borst, T. and Limani, F. (2020) ‘Patterns for searching data on the web across different research communities’, LIBER Quarterly: The Journal of the Association of European Research Libraries, 30(1), pp. 121. Available at: 10.18352/lq.10317
  8. 8Brickley, D., Burgess, M. and Noy, N. (2019) ‘Google dataset search: Building a search engine for datasets in an open web ecosystem’, in The World Wide Web Conference. New York, NY: Association for Computing Machinery, pp. 13651375. Available at: 10.1145/3308558.3313685
  9. 9Bugaje, M. and Chowdhury, G. (2018a) ‘Data retrieval = text retrieval?’, in G. Chowdhury, J. McLeod, V. Gillet, and P. Willett (eds.), Transforming Digital Worlds. Presented at the iConference 2018. Cham: Springer International Publishing, pp. 253262. Available at: 10.1007/978-3-319-78105-1_29
  10. 10Bugaje, M. and Chowdhury, G. (2018b) ‘Identifying design requirements of a user-centered research data management system’, in M. Dobreva, A. Hinze, and M. Žumer (eds.), Maturity and Innovation in Digital Libraries. Presented at the ICADL 2018. Cham: Springer International Publishing, pp. 335347. Available at: 10.1007/978-3-030-04257-8_35
  11. 11Burton, A. et al. (2017) ‘The Scholix framework for interoperability in data-literature information exchange’, D-Lib Magazine, 23(1/2). Available at: 10.1045/january2017-burton
  12. 12Cope, J. and Baker, J. (2017) ‘Library carpentry: Software skills training for library professionals’, International Journal of Digital Curation, 12(2), pp. 266273. Available at: 10.2218/ijdc.v12i2.576
  13. 13Cox, A. (2018) ‘Academic librarianship as a data profession: The familiar and unfamiliar in the data role spectrum’, eLucidate, 15(1–2). Available at: https://elucidate-ukeig.org.uk/index.php/elucidate/article/view/251 (Accessed: 3 November 2023).
  14. 14Cox, A. (2023) ‘How artificial intelligence might change academic library work: Applying the competencies literature and the theory of the professions’, Journal of the Association for Information Science and Technology, 74(3), pp. 367380. Available at: 10.1002/asi.24635
  15. 15Cox, A.M. et al. (2017) ‘Developments in research data management in academic libraries: Towards an understanding of research data service maturity’, Journal of the Association for Information Science and Technology, 68(9), pp. 21822200. Available at: 10.1002/asi.23781
  16. 16Cox, A.M. et al. (2019) ‘Maturing research data services and the transformation of academic libraries’, Journal of Documentation, 75(6), pp. 14321462. Available at: 10.1108/JD-12-2018-0211
  17. 17Cruz, M. et al. (2019) ‘Policy needs to go hand in hand with practice: The learning and listening approach to data management’, Data Science Journal, 18(1), p. 45. Available at: 10.5334/dsj-2019-045
  18. 18Cruz, M.J. et al. (2018) ‘From passive to active, from generic to focussed: How can an institutional data archive remain relevant in a rapidly evolving landscape?’, International Journal of Digital Curation, 13(1), pp. 385391. Available at: 10.2218/ijdc.v13i1.613
  19. 19Curty, R.G. (2016) ‘Factors influencing research data reuse in the social sciences: An exploratory study’, International Journal of Digital Curation, 11(1), pp. 96117. Available at: 10.2218/ijdc.v11i1.401
  20. 20Darch, P.T. et al. (2020) ‘Library cultures of data curation: Adventures in astronomy’, Journal of the Association for Information Science and Technology, 71(12), pp. 14701483. Available at: 10.1002/asi.24345
  21. 21Färber, M. and Lamprecht, D. (2021) ‘The data set knowledge graph: Creating a linked open data source for data sets’, Quantitative Science Studies, 2(4), pp. 13241355. Available at: 10.1162/qss_a_00161
  22. 22Friedrich, T. (2020) Looking for data: Information seeking behaviour of survey data users. PhD thesis., Humboldt-Universität zu Berlin. Available at: https://edoc.hu-berlin.de/handle/18452/22813 (Accessed: 10 March 2022).
  23. 23Garnett, A. et al. (2017) ‘Open metadata for research data discovery in Canada’, Journal of Library Metadata, 17(3–4), pp. 201217. Available at: 10.1080/19386389.2018.1443698
  24. 24Gowen, E. and Meier, J.J. (2020) ‘Research data management services and strategic planning in libraries today: A longitudinal study’, Journal of Librarianship and Scholarly Communication, 8(1), p. eP2336. Available at: 10.7710/2162-3309.2336
  25. 25Gregory, K. (2020) ‘A dataset describing data discovery and reuse practices in research’, Scientific Data, 7(1), p. 232. Available at: 10.1038/s41597-020-0569-5
  26. 26Gregory, K. et al. (2020) ‘Lost or found? Discovering data needed for research’, Harvard Data Science Review, 2(2). Available at: 10.1162/99608f92.e38165eb
  27. 27Gregory, K.M. et al. (2019) ‘Understanding data search as a socio-technical practice’, Journal of Information Science, 46(4), pp. 459475. Available at: 10.1177/0165551519837182
  28. 28Hedeland, H. (2020) ‘Providing digital infrastructure for audio-visual linguistic research data with diverse usage scenarios: Lessons learnt’, Publications, 8(2), p. 33. Available at: 10.3390/publications8020033
  29. 29Hemphill, L. et al. (2022) ‘How do properties of data, their curation, and their funding relate to reuse?’, Journal of the Association for Information Science and Technology, 73(10), pp. 14321444. Available at: 10.1002/asi.24646
  30. 30Huang, Y., Cox, A.M. and Sbaffi, L. (2021) ‘Research data management policy and practice in Chinese university libraries’, Journal of the Association for Information Science and Technology, 72(4), pp. 493506. Available at: 10.1002/asi.24413
  31. 31Jaradeh, M.Y. et al. (2019) ‘Open research knowledge graph: A system walkthrough’, in A. Doucet, A. Isaac, K. Golub, T. Aalberg, and A. Jatowt (eds.), Digital Libraries for Open Knowledge. Cham: Springer International Publishing, pp. 348351. Available at: 10.1007/978-3-030-30760-8_31
  32. 32Joo, S., Kim, S. and Kim, Y. (2017) ‘An exploratory study of health scientists’ data reuse behaviors: Examining attitudinal, social, and resource factors’, Aslib Journal of Information Managagement, 69, pp. 389407. Available at: 10.1108/AJIM-12-2016-0201
  33. 33Joo, S. and Schmidt, G.M. (2021) ‘Research data services from the perspective of academic librarians’, Digital Library Perspectives, 37(3), pp. 242256. Available at: 10.1108/DLP-10-2020-0106
  34. 34Joo, Y.K. and Kim, Y. (2017) ‘Engineering researchers’ data reuse behaviours: a structural equation modelling approach’, The Electronic Library, 35, pp. 11411161. Available at: 10.1108/EL-08-2016-0163
  35. 35Kacprzak, E. et al. (2018) ‘Characterising dataset search queries’, in Companion Proceedings of the The Web Conference 2018. Republic and Canton of Geneva, CHE: International World Wide Web Conferences Steering Committee, pp. 14851488. Available at: 10.1145/3184558.3191597
  36. 36Khan, N., Thelwall, M. and Kousha, K. (2021) ‘Are data repositories fettered? A survey of current practices, challenges and future technologies’, Online Information Review, ahead-of-print(ahead-of-print). Available at: 10.1108/OIR-04-2021-0204
  37. 37Kim, Y. (2017) ‘Fostering scientists’ data sharing behaviors via data repositories, journal supplements, and personal communication methods’, Information Processing & Managagement, 53, pp. 871885. Available at: 10.1016/j.ipm.2017.03.003
  38. 38Koesten, L.M. et al. (2017) ‘The trials and tribulations of working with structured data: A study on information seeking behaviour’, in Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. New York, NY: Association for Computing Machinery, pp. 12771289. Available at: 10.1145/3025453.3025838
  39. 39Krämer, T., Papenmeier, A., Carevic, Z., Kern, D. and Mathiak, B. (2021) ‘Data-Seeking Behaviour in the Social Sciences’, International Journal on Digital Libraries, 22(2), pp. 175195. Available at: 10.1007/s00799-021-00303-0
  40. 40Lafia, S. et al. (2021) ‘Leveraging machine learning to detect data curation activities’, in 2021 IEEE 17th International Conference on eScience (eScience). Presented at the 2021 IEEE 17th International Conference on eScience (eScience). Innsbruck, Austria: IEEE, pp. 149158. Available at: 10.1109/eScience51609.2021.00025
  41. 41Liu, S. et al. (2021) ‘An infrastructure with user-centered presentation data model for integrated management of materials data and services’, npj Computational Materials, 7(1), pp. 18. Available at: 10.1038/s41524-021-00557-x
  42. 42Lund, B.D. et al. (2020) ‘Perceptions toward artificial intelligence among academic library employees and alignment with the diffusion of innovations’ adopter categories’, College & Research Libraries, 81(5), pp. 865882. Available at: 10.5860/crl.81.5.865
  43. 43Manghi, P. et al. (2019) The OpenAIRE research graph data model. Available at: 10.5281/zenodo.2643199
  44. 44Mannheimer, S. et al. (2021) ‘Dataset search: A lightweight, community-built tool to support research data discovery’, Journal of eScience Librarianship, 10(1), p. e1189. Available at: 10.7191/jeslib.2021.1189
  45. 45Marlina, E. and Purwandari, B. (2019) ‘Strategy for research data management services in Indonesia’, Procedia Computer Science, 161, pp. 788796. Available at: 10.1016/j.procs.2019.11.184
  46. 46Mathiak, B. et al. (2023) ‘What are researchers’ needs in data discovery? Analysis and ranking of a large-scale collection of crowdsourced use cases’, Data Science Journal, 22(1), p. 3. Available at: 10.5334/dsj-2023-003
  47. 47Mulongo, J. et al. (2022) ‘Investigation of research data maturity in academic libraries of developed countries’, in Proceedings of the 15th International Conference on Theory and Practice of Electronic Governance. New York, NY: Association for Computing Machinery, pp. 288300. Available at: 10.1145/3560107.3560153
  48. 48R Core Team. (n.d.) R: a language and environment for statistical computing. Available at https://www.gbif.org/tool/81287/r-a-language-and-environment-for-statistical-computing (Accessed 13 July 2022).
  49. 49Read, K. et al. (2015) ‘Promoting data reuse and collaboration at an academic medical center’, International Journal of Digital Curation, 10(1), pp. 260267. Available at: 10.2218/ijdc.v10i1.366
  50. 50Reichmann, S. et al. (2021) ‘Between administration and research: Understanding data management practices in an institutional context’, Journal of the Association for Information Science and Technology, 72(11), pp. 14151431. Available at: 10.1002/asi.24492
  51. 51Savage, J.L. and Cadwallader, L. (2019) ‘Establishing, developing, and sustaining a community of data champions’, Data Science Journal, 18(1), p. 23. Available at: 10.5334/dsj-2019-023
  52. 52Sharifpour, R., Wu, M. and Zhang, X. (2022) ‘Large-scale analysis of query logs to profile users for dataset search’, Journal of Documentation, ahead-of-print(ahead-of-print). Available at: 10.1108/JD-12-2021-0245
  53. 53Sheridan, H. et al. (2021) ‘Data curation through catalogs: A repository-independent model for data discovery’, Journal of eScience Librarianship, 10(3). Available at: 10.7191/jeslib.2021.1203
  54. 54Si, L. et al. (2019) ‘Investigation and analysis of research support services in academic libraries’, The Electronic Library, 37(2), pp. 281301. Available at: 10.1108/EL-06-2018-0125
  55. 55Smit, M. (2019) ‘Code convention adherence in research data infrastructure software: An exploratory study’, in 2019 IEEE International Conference on Big Data (Big Data). Presented at the 2019 IEEE International Conference on Big Data (Big Data). pp. 46914700. Available at: 10.1109/BigData47090.2019.9006130
  56. 56Sun, G. (2019) Knowledge representation of social science quantitative research data for data curation and reuse. PhD thesis. Nanyang Technological University. Available at: https://dr.ntu.edu.sg/handle/10356/107575 (Accessed 12 July 2022).
  57. 57Tammaro, A.M. et al. (2019) ‘Data curator’s roles and responsibilities: An international perspective’, Libri, 69(2), pp. 89104. Available at: 10.1515/libri-2018-0090
  58. 58Tang, R. and Hu, Z. (2019) ‘Providing research data management (RDM) services in libraries: Preparedness, roles, challenges, and training for RDM practice’, Data and Information Management, 3(2), pp. 84101. Available at: 10.2478/dim-2019-0009
  59. 59Teperek, M., Cruz, M. and Kingsley, D. (2022) ‘Time to re-think the divide between academic and support staff’, Nature. Available at: 10.1038/d41586-022-01081-8
  60. 60Vardigan, M., Heus, P. and Thomas, W. (2008) ‘Data documentation initiative: Toward a standard for the social sciences’, International Journal of Digital Curation, 3(1), pp. 107113. Available at: 10.2218/ijdc.v3i1.45
  61. 61Wilkinson, M.D. et al. (2016) ‘The FAIR guiding principles for scientific data management and stewardship’, Scientific Data, 3(1), p. 160018. Available at: 10.1038/sdata.2016.18
  62. 62Wilson, L., Colborne, A. and Smit, M. (2017) ‘Preparing data managers to support open ocean science: Required competencies, assessed gaps, and the role of experiential learning’, Presented at the 2017 IEEE International Conference on Big Data (Big Data). IEEE Computer Society, pp. 39843993. Available at: 10.1109/BigData.2017.8258412
  63. 63Wu, M. et al. (2019) ‘Data discovery paradigms: User requirements and recommendations for data repositories’, Data Science Journal, 18(1), p. 3. Available at: 10.5334/dsj-2019-003
  64. 64Yoon, A. (2017) ‘Role of communication in data reuse’, Proceedings of the Association for Information Science and Technology, 54, pp. 463471. Available at: 10.1002/pra2.2017.14505401050
  65. 65Yoon, A. and Lee, Y.Y. (2019) ‘Factors of trust in data reuse’, Online Information Review, 43, pp. 12451262. Available at: 10.1108/oir-01-2019-0014
Language: English
Submitted on: Nov 21, 2023
Accepted on: Sep 10, 2024
Published on: Oct 8, 2024
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2024 Guangyuan Sun, Tanja Friedrich, Kathleen Gregory, Brigitte Mathiak, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.