Identifying Design Requirements of a User-Centered Research Data Management System

  • Maryam Bugaje
  • Gobinda ChowdhuryEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11279)


Research data repositories perform many useful functions, the key ones being the storage of research datasets, and making the same discoverable for potential reuse. Over the years, various criteria for assessing the user-centeredness of information systems have been developed and standards have gradually been improved. However, there has been less development in case of research data management (RDM) systems. By means of a combination of user-focused research methods viz. questionnaire surveys, face-to-face interviews, a systematic appraisal of existing services and a technical experiment, we have sought to understand the meaning of user-centeredness pertaining to research data repositories, and identify some key indicators of it. We have furthermore translated our findings into design requirements based on which we propose to develop and test a prototype of a user-centered RDM system. This paper reports on how we identified the design requirements that would make the RDM systems more user-centered.


User-Centered design Research data management Information retrieval Metadata Research data repositories Scientific data 


  1. 1.
    Arend, D., Lange, M., Chen, J., et al.: e! DAL - a framework to store, share and publish research data. BMC Bioinform. 15(1), 214 (2014). Scholar
  2. 2.
    Curdt, C., Hoffmeister, D.: Research data management services for a multidisciplinary, collaborative research project: design and implementation of the TR32DB project database. Program Electron. Libr. Inf. Syst. 49(4), 494–512 (2015). Scholar
  3. 3.
    Cox, A., Pinfield, S.: Research data management and libraries: current activities and future priorities. J. Libr.Google Scholar
  4. 4.
    Amorim, R., Castro, J., da Silva, R.J., Ribeiro, C.: A comparison of research data management platforms: architecture, flexible metadata and interoperability. Univers. Access Inf. Soc. 16(4), 851–862 (2016). Scholar
  5. 5.
    Patel, D.: Research data management: a conceptual framework. Libr. Rev. 65(4/5), 226–241 (2016)CrossRefGoogle Scholar
  6. 6.
    Perrino, T., et al.: Advancing Science Through Collaborative Data Sharing and Synthesis. Perspect. Psychol. Sci. 8(4), 433–444 (2013)CrossRefGoogle Scholar
  7. 7.
    The Royal Society: Science as an open enterprise (2012). Accessed 11 June 2018
  8. 8.
    Borgman, C.: The conundrum of sharing research data. SSRN Electron. J. (2011)Google Scholar
  9. 9.
    Costello, M.: Motivating online publication of data. Bioscience 59(5), 418–427 (2009)CrossRefGoogle Scholar
  10. 10.
    Faniel, I., Jacobsen, T.: Reusing scientific data: how earthquake engineering researchers assess the reusability of colleagues’ data. Comput. Support. Coop. Work. (CSCW) 19(3–4), 355–375 (2010)CrossRefGoogle Scholar
  11. 11.
    Carlson, J.: Demystifying the data interview: developing a foundation for reference librarians to talk with researchers about their data. Ref. Serv. Rev. 40(1), 7–23 (2012). Scholar
  12. 12.
    Mückschel, C., Nieschulze, J., Weist, C., Sloboda, B., Köhler, W.: Herausforderungen, Probleme und Lösungsansätze im Datenmanagement von Sonderforschungsbereichen. In: eZAI (elektronische Zeitschrift für Agrarinformatik), vol. 2, pp. 1–16 (2007)Google Scholar
  13. 13.
    Curdt, C., Hoffmeister, D., Waldhoff, G., Jekel, C., Bareth, G.: Scientific research data management for soil-vegetation-atmosphere data – the TR32DB. Int. J. Digit. Curation 7(2), 68–80 (2012). Scholar
  14. 14.
    bioCADDIE | biomedical and healthCAre Data Discovery and Indexing Ecosystem. Accessed 12 June 2018
  15. 15.
    Research Data Discovery Service: Laying the firm foundations for a Jisc UK Research Data Discovery Service. Accessed 12 June 2018
  16. 16.
    Bugaje, M., Chowdhury, G.: Is data retrieval different from text retrieval? An exploratory study. In: Choemprayong, S., Crestani, F., Cunningham, S.J. (eds.) ICADL 2017. LNCS, vol. 10647, pp. 97–103. Springer, Cham (2017). Scholar
  17. 17.
    Bugaje, M., Chowdhury, G.: Data retrieval = text retrieval? In: Chowdhury, G., McLeod, J., Gillet, V., Willett, P. (eds.) iConference 2018. LNCS, vol. 10766, pp. 253–262. Springer, Cham (2018). Scholar
  18. 18.
    Whyte, A., Tedds, J.: Making the case for research data management. Digital Curation Centre, dccacuk (2011). Accessed 12 June 2018
  19. 19.
    Santos, C., Blake, J., States, D.: Supplementary data need to be kept in public repositories. Nature 438(7069), 738 (2005). Scholar
  20. 20.
    Sallans, A., Lake, S.: Data management assessment and planning tools. In: Research Data Management: Practical Strategies for Information Professionals. pp. 87–107. Purdue University Press, West Lafayette (2014)Google Scholar
  21. 21.
    Dumontier, M., Gray, A., Marshall, M., et al.: The health care and life sciences community profile for dataset descriptions. PeerJ 4 (2016). Scholar
  22. 22.
    UK Research and Innovation: Concordat on Open Research Data (2016). Accessed 13 June 2018
  23. 23.
    Boeckhout, M., Zielhuis, G., Bredenoord, A.: The FAIR guiding principles for data stewardship: fair enough? Eur. J. Hum. Genet. 26(7), 931–936 (2018). Scholar
  24. 24.
    Starr, J., Castro, E., Crosas, M., et al.: Achieving human and machine accessibility of cited data in scholarly publications. PeerJ Comput. Sci. 1, e1 (2015). Scholar
  25. 25.
    Alsos, O.A., Svanæs, D.: Designing for the secondary user experience. In: Campos, P., Graham, N., Jorge, J., Nunes, N., Palanque, P., Winckler, M. (eds.) INTERACT 2011. LNCS, vol. 6949, pp. 84–91. Springer, Heidelberg (2011). Scholar
  26. 26.
    Bugaje, M., Chowdhury, G.: Towards a more user-centered design of research data management (RDM) systems [abstract]. In: Information: Interactions and Impact (i3), Aberdeen, 27–30 June 2017, pp. 53–55 (2017)Google Scholar
  27. 27.
    Taylor, R.: Question-negotiation and information seeking in libraries. Coll. Res. Libr. 76(3), 251–267 (2015). Scholar
  28. 28.
    Morris, R.: Toward a user-centered information service. J. Am. Soc. Inf. Sci. 45(1), 20–30 (1994).;2-nCrossRefGoogle Scholar
  29. 29.
    Willis, C., Greenberg, J., White, H.: Analysis and synthesis of metadata goals for scientific data. J. Am. Soc. Inf. Sci. Technol. 63(8), 1505–1520 (2012). Scholar
  30. 30.
    Van Noorden, R.: Data-sharing: everything on display. Nature 500(7461), 243–245 (2013). Scholar
  31. 31.
    Chowdhury, G., Walton, G., Bugaje, M.: Research data management: practices, skills and training needs of university researchers in the UK. In: Špiranec, S., Bartol, T., Stopar, K., Boh Podgornik, B. (eds.) 2017 Fifth European Conference on Information Literacy (ECIL), p. 30. Information Literacy Association (InLitAs), Saint-Malo (2017)Google Scholar
  32. 32.
    Bugaje, M., Chowdhury, G: Disciplinary contexts in research data management: a case-study of three disciplines (accepted contribution). In: Fifth European Conference on Information Literacy (ECIL), Finland (2018)Google Scholar
  33. 33.
    Borgman, C.: Big Data, Little Data, No Data, 1st edn, pp. 81–161. The MIT Press, Cambridge (2015)Google Scholar
  34. 34.
    Boru, D., Kliazovich, D., Granelli, F., Bouvry, P., Zomaya, A.Y.: Energy-efficient data replication in cloud computing datacenters. Clust. Comput. 18(1), 385–402 (2015)CrossRefGoogle Scholar
  35. 35.
    Chowdhury, G.G.: Sustainability of Scholarly Information. Facet Publishing, London (2014)Google Scholar
  36. 36.
    Weber, A., Piesche, C.: Requirements on long-term accessibility and preservation of research results with particular regard to their provenance. ISPRS Int. J. Geo-Inf. 5, 49 (2016)CrossRefGoogle Scholar
  37. 37.
    Research Information Network (RIN): To Share or not to Share: Publication and Quality Assurance of Research Data Outputs, p. 48 (2008). Accessed 25 June 2018
  38. 38.
    Rumsey, S., Jefferies, N.: Challenges in building an institutional research data catalogue. Int. J. Digit. Curation 8(2), 205–214 (2013). Scholar
  39. 39.
    Weibel, S.: The Dublin Core: a simple content description model for electronic resources. Bull. Am. Soc. Inf. Sci. Technol. 24(1), 9–11 (2005). Scholar

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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Computer and Information SciencesNorthumbria UniversityNewcastleUK

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