Bibliometric-Enhanced Information Retrieval: 2nd International BIR Workshop

  • Philipp Mayr
  • Ingo Frommholz
  • Andrea Scharnhorst
  • Peter Mutschke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9022)

Abstract

This workshop brought together experts of communities which often have been perceived as different: bibliometrics / scientometrics / informetrics on the one side and information retrieval on the other. Our motivation as organizers of the workshop started from the observation that main discourses in both fields are different, that communities are only partly overlapping and from the belief that a knowledge transfer would be profitable for both sides. Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, although they offer value-added effects for users. On the other hand, more and more information professionals, working in libraries and archives are confronted with applying bibliometric techniques in their services. This way knowledge exchange becomes more urgent. The first workshop set the research agenda, by introducing methods, reporting about current research problems and brainstorming about common interests. This follow-up workshop continued the overall communication, but also put one problem into the focus. In particular, we explored how statistical modelling of scholarship can improve retrieval services for specific communities, as well as for large, cross-domain collections like Mendeley or ResearchGate. This second BIR workshop continued to raise awareness of the missing link between Information Retrieval (IR) and bibliometrics and contributes to create a common ground for the incorporation of bibliometric-enhanced services into retrieval at the scholarly search engine interface.

Keywords

Bibliometrics Scientometrics Informetrics Information Retrieval Digital Libraries 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Abbasi, M.K., Frommholz, I.: Cluster-based Polyrepresentation as Science Modelling Approach for Information Retrieval. Scientometrics (2015), doi:10.1007/s11192-014-1478-1Google Scholar
  2. 2.
    Jack, K., López-García, P., Hristakeva, M., Kern, R.: {{citation needed}}: Filling in Wikipedia’s Citation Shaped Holes. In: Bibliometric-Enhanced Information Retrieval, ECIR, Amsterdam (2014), http://ceur-ws.org/Vol-1143/paper6.pdf (retrieved from)
  3. 3.
    Mayr, P., Schaer, P., Scharnhorst, A., Mutschke, P.: Editorial for the Bibliometric-enhanced Information Retrieval Workshop at ECIR 2014. In: de Rijke, M., Kenter, T., de Vries, A.P., Zhai, C., de Jong, F., Radinsky, K., Hofmann, K. (eds.) ECIR 2014. LNCS, vol. 8416, pp. 1–4. Springer, Heidelberg (2014b), http://ceur-ws.org/Vol-1143/editorial.pdf CrossRefGoogle Scholar
  4. 4.
    Mayr, P., Scharnhorst, A.: Scientometrics and Information Retrieval - weak-links revitalized. Scientometrics (2015), doi:10.1007/s11192-014-1484-3Google Scholar
  5. 5.
    Mayr, P., Scharnhorst, A., Larsen, B., Schaer, P., Mutschke, P.: Bibliometric-enhanced Information Retrieval. In: de Rijke, M., Kenter, T., de Vries, A.P., Zhai, C., de Jong, F., Radinsky, K., Hofmann, K. (eds.) ECIR 2014. LNCS, vol. 8416, pp. 798–801. Springer, Heidelberg (2014a), doi:10.1007/978-3-319-06028-6_99CrossRefGoogle Scholar
  6. 6.
    Mutschke, P., Mayr, P., Schaer, P., Sure, Y.: Science models as value-added services for scholarly information systems. Scientometrics 89(1), 349–364 (2011), doi:10.1007/s11192-011-0430-xCrossRefGoogle Scholar
  7. 7.
    White, H.D., McCain, K.W.: Visualizing a discipline: An author co-citation analysis of information science, 1972–1995. Journal of the American Society for Infor-mation Science 49, 327–355 (1998)Google Scholar
  8. 8.
    Wolfram, D.: The Symbiotic Relationship Between Information Retrieval and Informetrics. Scientometrics (2015), doi:10.1007/s11192-014-1479-0Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Philipp Mayr
    • 1
  • Ingo Frommholz
    • 2
  • Andrea Scharnhorst
    • 3
  • Peter Mutschke
    • 1
  1. 1.GESIS - Leibniz Institute for the Social SciencesCologneGermany
  2. 2.Department of Computer Science and TechnologyUniversity of BedfordshireLutonUK
  3. 3.Royal Netherlands Academy of Arts and Sciences (DANS)AmsterdamThe Netherlands

Personalised recommendations