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Combining Bibliometrics and Information Retrieval

Workshop at ISSI 2013

15 July 2013 - 10:00 to 12:30

You are invited to participate in the upcoming workshop on Combining Bibliometrics and Information Retrieval, to be held as part of the 14th International Society of Scientometrics and Informetrics Conference (ISSI).

News from 2015-03-09: Some of the papers presented at the workshop have been published in a special issue in Scientometrics recently. See the list of papers.

Pictures from the Workshop

Workshop Program


Introduction "Combining Bibliometrics and Information Retrieval" (Mayr, Schaer) [PDF]


Invited papers on the workshop topic (10-15 min talk + discussion)

  • Wolfgang Glänzel (KU Leuven): "Bibliometrics-aided retrieval" [PDF]
  • Michel Zitt (INRA France): "Meso-level retrieval: field delineation and hybrid methods" [PDF]
  • Dietmar Wolfram (University of Wisconsin-Milwaukee): "The symbiotic relationship of bibliometrics and information retrieval" [PDF]
  • Howard D. White (Drexel University): "Co-cited Author Maps, Bibliographic Retrievals, and a Viennese Author" [PDF]
  • Birger Larsen (Royal School of Library and Information Science Copenhagen): "The iSearch test collection - an Information Retrieval benchmark with citations" [PDF] [Link to iSearch]


Moderated panel discussion (2-3 minute initials statements from the panelists, then prepared questions by Scharnhorst, Mayr, Schaer)


Sum up and future actions (workshop organizers)


Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, yet they offer value-added effects for users. How can we build scholarly information systems that explicitly use them at the user-system interface?

We propose a half-day workshop that addresses this question. It will involve keynote talks, research project reports, demonstrations, and a panel discussion on next-generation services. Our interests include information retrieval, information seeking, science modelling, network analysis, and digital libraries. The goal is to apply insights from bibliometrics, scientometrics, and informetrics to concrete, practical problems of information retrieval and browsing.

Retrieval evaluations have shown that simple text-based retrieval methods scale up well but do not progress. Traditional retrieval has reached a high level in terms of measures like precision and recall, but scientists and scholars still face challenges present since the early days of digital libraries: mismatches between search terms and indexing terms, overload from result sets that are too large and complex, and the drawbacks of text-based relevance rankings. Therefore we will focus on a new approach to improve retrievals in digital library systems: science models.

By science models, we understand statistical analyses and corresponding visualizations of the evolving science system. Such analyses have revealed not only the fundamental laws of Bradford and Lotka, but also network structures and dynamic mechanisms in scientific production. Science models are increasingly used to evaluate specialties, to forecast and discover research trends, and to shape science policy. Their use as tools in navigating scientific information in public digital libraries is a promising but still relatively new development. We will explore how network analysis, statistical modelling, and mapping of scholarship can improve retrieval services for specific communities, as well as for large, cross-domain collections. Some of these techniques are already used in working systems; others are envisioned for the future. We will ask: how can models of science be interrelated with scholarly, task-oriented searching? And can insights from searching improve the science models themselves?

Although information retrieval and scientometrics belong to one discipline, they are driven by different epistemic perspectives. In the past, experts from both sides have called for closer collaboration, but their encounters are rather ad-hoc. This workshop aims to raise awareness of the missing link and to create a common ground for the incorporation of science models
into retrieval at the digital library interface.


  • Philipp Mayr, GESIS - Leibniz Institute for the Social Sciences, Germany
  • Philipp Schaer, GESIS - Leibniz Institute for the Social Sciences, Germany
  • Peter Mutschke, GESIS - Leibniz Institute for the Social Sciences, Germany
  • Andrea Scharnhorst, DANS, Royal Netherlands Academy of Arts and Sciences in Amsterdam, Netherlands
  • Howard D. White, College of Information Science and Technology, Drexel University, USA