2nd International Workshop on Bibliometric-enhanced Information Retrieval (BIR2015)

Important Dates

• Submissions: 08 February 2015 (extended)
• Notification: 27 February 2015
• Camera Ready Contributions: 13 March 2015
• Workshop: 29 March 2015 in Vienna, Austria

Introduction

Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, although they offer value-added effects for users. In this workshop we will explore how statistical modelling of scholarship, such as Bradfordizing or network analysis of coauthorship network, or simple citation graphs, can improve retrieval services for specific communities, as well as for large, cross-domain collections like Mendeley. This workshop aims to raise awareness of the missing link between Information Retrieval (IR) and bibliometrics/scientometrics and to create a common ground for the incorporation of bibliometric-enhanced services into retrieval at the scholarly search engine interface.

The second BIR workshop (BIR2015) addresses scholarly and explicitly industrial researchers. 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.

Aim of the Workshop

In this second workshop (see papers and presentations of the first workshop) we aim to engage with the IR community about possible links to bibliometrics and complex network theory which also explores networks of scholarly communication. Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, yet they offer value-added effects for users. 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 statistical modelling 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. Statistical models of scholarly activities 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 statistical modelling 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 but not well integrated in larger scholarly IR environments.

The availability of new IR test collections that contain citation and bibliographic information like the iSearch collection or the ACL collection could deliver enough ground to interest (again) the IR community in these kind of bibliographic systems. The long-term research goal is to develop and evaluate new approaches based on informetrics and bibliometrics.

The aim of this workshop is to bring together researchers from different domains, such as information retrieval, information seeking, science modelling, bibliometrics, scientometrics, network analysis, and digital libraries to move toward a deeper understanding of this research challenge.

Workshop Topics

To support the previously described goals the workshop topics include (but are not limited to) the following:

• IR for digital libraries and scientific information portals
• IR for scientific domains, e.g. social sciences, life sciences etc.
• Information Seeking Behaviour
• Bibliometrics, citation analysis and network analysis for IR
• Query expansion and relevance feedback approaches
• Science Modelling (both formal & empirical)
• Task based user modelling, interaction, and personalisation
• (Long-term) Evaluation methods and test collection design
• Collaborative information handling and information sharing
• Classification, categorisation and clustering approaches
• Information extraction (including topic detection, entity and relation extraction)
• Recommendations based on explicit and implicit user feedback

We especially invite descriptions of running projects and ongoing work. Papers that investigate multiple themes directly are especially welcome.

Submission Details

All submissions must be written in English following Springer LNCS author guidelines (4 to 8 pages) and should be submitted as PDF files to EasyChair. All submissions will be reviewed by at least two independent reviewers. Please be aware of the fact that at least one author per paper needs to register for the workshop and attend the workshop to present the work. In case of no-show the paper (even if accepted) will be deleted from the proceedings AND from the program.

Springer LNCS: http://www.springer.com/lncs

EasyChair: https://easychair.org/conferences/?conf=bir20150

Workshop proceedings will be deposited online in the CEUR workshop proceedings publication service (ISSN 1613-0073) - This way the proceedings will be permanently available and citable (digital persistent identifiers and long term preservation).

Programm Committee 

• Marc Bertin, Université du Québec à Montréal (Canada)
• José Borbinha, INESC-ID/IST (Portugal)
• Guillaume Cabanac, University of Toulouse (France)
• Cornelia Caragea, University of North Texas (USA)
• Martine De Cock, Ghent University (Belgium)
• Ed A. Fox, Virginia Tech (USA)
• Norbert Fuhr, University of Duisburg-Essen(Germany)
• Björn Hammarfelt, University of Borås (Sweden)
• Peter Ingwersen, University of Copenhagen (Denmark)
• C. Lee Giles, Pennsylvania State University (USA)
• Birger Larsen, Aalborg University (Denmark)
• Claus-Peter Klas, University of Hagen (Germany)
• Kris Jack, Mendeley (UK)
• Stasa Milojevic, Indiana University (USA)
• Stephen Robertson, University College London (UK)
• Philipp Schaer, GESIS (Germany)
• Henry Small, SciTech Stategies (USA)
• Lynda Tamine-Lechani, University Paul Sabatier (France)
• Simone Teufel, University of Cambridge (UK)
• Howard D. White, Drexel University (USA)
• Ludo Waltman, CWTS (NL)
• Dietmar Wolfram, University of Wisconsin (USA)

This workshop is also informed by an ongoing COST Action TD1210 KnowEscape.

Organizers

• Philipp Mayr, GESIS - Leibniz Institute for the Social Sciences, German
• Ingo Frommholz, University of Bedfordshire in Luton, UK
• Peter Mutschke, GESIS - Leibniz Institute for the Social Sciences, Germany
• Andrea Scharnhorst, DANS, Royal Netherlands Academy of Arts and Sciences in Amsterdam, Netherlands

Workshop Program

10:00-10:15

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

10:15-11:30

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]

11:30-12:15

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

• Howard D. White  (Drexel University)
• Wolfgang Glänzel (KU Leuven)
• Birger Larsen (Royal School of Library and Information Science Copenhagen)
• Dietmar Wolfram (University of Wisconsin-Milwaukee)
• Michel Zitt (INRA France)

12:15-12:30

Sum up and future actions (workshop organizers)

Scope

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.

Organizers

• 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