[Sigmetrics] Deadline extension 25 April: Joint workshop on Bibliometric-enhanced IR and NLP for Digital Libraries (BIRNDL) @JCDL2016

Mayr-Schlegel, Philipp Philipp.Mayr-Schlegel at gesis.org
Sun Apr 17 16:09:50 EDT 2016


== Final Call for Papers ==
You are invited to participate in the upcoming Joint workshop on Bibliometric-enhanced IR and NLP for Digital Libraries (BIRNDL), to be held as part of the Joint Conference on Digital Libraries 2016 (JCDL 2016) in Newark, New Jersey, USA.

We are happy to announce that our first keynote will be given by Dietmar Wolfram (University of Wisconsin-Milwaukee): "Bibliometrics, Information Retrieval and Natural Language Processing: Natural Synergies to Support Digital Library Research".

<http://wing.comp.nus.edu.sg/birndl-jcdl2016/>

The past BIR and NLPIR4DL organizers are proposing this workshop at JCDL together. In conjunction with the workshop, we will hold the 2nd CL-SciSumm Shared Task in Scientific Document Summarization.  <http://wing.comp.nus.edu.sg/cl-scisumm2016/>
Reports from the shared task systems will be featured as part of a session at the workshop.

=== Important Dates ===
- Submissions: 25 April 2016 (extended)
- Notification: 16 May 2016
- Camera Ready Contributions: 09 June 2016
- Workshop: 23 June 2016 in Newark, New Jersey, USA

=== Aim of the Workshop ===
Current digital libraries collect and allow access to digital papers and their metadata (including citations), but mostly do not analyze the items they index. The large scale of scholarly publications poses a challenge for scholars in their search for relevant literature. Searchers of digital libraries, citation indices and journal databases are inundated with thousands of results. The community needs to develop techniques to better support both basic as well as higher-order information seeking and scholarly sensemaking activities.

The BIRNDL 2016 workshop is a joint scientific event gathering scholars from the BIR (Bibliometric-enhanced Information Retrieval) and the NLPIR4DL (Text and citation analysis for scholarly digital libraries) communities. The scope of BIRNDL is on scholarly publications and data - the explosion in the production of scientific literature and the growth of scientific enterprise; its consistent exponential growth approaches an empirical law. The workshop will investigate how natural language processing, information retrieval, scientometric and recommendation techniques can advance the state-of-the-art in scholarly document understanding, analysis and retrieval at scale. Researchers are in need of assistive technologies to track developments in an area, identify the approaches used to solve a research problem over time and summarize research trends. Digital libraries require semantic search, question-answering and automated recommendation and reviewing systems to manage and retrieve answers from scholarly databases. Full document text analysis can help to design semantic search, translation and summarization systems; citation and social network analyses can help digital libraries to visualize scientific trends, bibliometrics and relationships and influences of works and authors. All these approaches can be supplemented with the metadata supplied by digital libraries, inclusive of usage data, such as download counts.

This workshop will be relevant to scholars in the cross-disciplinary field of Computer Science and Digital Libraries, in particular in the research areas of Natural Language Processing and in Information Retrieval; it will also be important for all stakeholders in the publication pipeline: implementers, publishers and policymakers. Even when only considering the scholarly sites within Computer Science, we find that the field is well-represented - ACM Portal, IEEE Xplore, Google Scholar, PSU's CiteSeerX, MSR's Academic Search, Elsevier's Mendeley, Tsinghua's ArnetMiner, Trier's DBLP, Hiroshima's PRESRI; with this workshop we hope to bring a number of these contributors together. Today's publishers continue to seek new ways to be relevant to their consumers, in disseminating the right published works to their audience. The fact that formal citation metrics have become an increasingly large factor in decision-making by universities and funding bodies worldwide makes the need for research in such topics and for better methods for measuring the impact of work more pressing.

This workshop is also informed by an ongoing COST Action TD1210 KnowEscape. http://www.knowescape.org

=== Workshop Topics ===
To support the previously described goals the workshop topics include (but are not limited to) the following:
- Information retrieval (IR) for digital libraries and scientific information portals
- IR for scholarly text, e.g. citation-based IR
- IR for scientific domains, e.g. social sciences, life sciences etc.
- Information Seeking Behaviour
- Navigation, searching and browsing in scholarly DLs; Niche search in scholarly DLs; New information access methods for scientific papers
- Query expansion and relevance feedback approaches
- Question-answering for scholarly DLs
- Recommendations based on explicit and implicit user feedback
- Recommendation for scholarly papers, reviewers, citations and publication venues
- (Social) Book Search
- Summarisation of scientific articles; Automatic creation of reviews and automatic qualitative assessment of submissions;
- Bibliometrics, citation analysis and network analysis for IR; Citation function/motivation analysis; Novel bibliographic metrics; Topical modeling analysis
- Knowledge discovery and analysis of the ancestry of ideas
- Metadata and controlled vocabularies for resource description and discovery; Automatic metadata discovery, such as language identification
- Translation, multilingual and multimedia analysis and alignment of scholarly works
- Analyses of writing style in scholarly publications
- Science Modelling (both formal and empirical)
- Task based user modelling, interaction, and personalisation
- (Long-term) Evaluation methods and test collection design
- Collaborative information handling and information sharing
- Disambiguation issues in scholarly DLs using NLP or IR techniques; Data cleaning and data quality
- Classification, categorisation and clustering approaches
- Information extraction (including topic detection, entity and relation extraction)

For the paper sessions we invite descriptions of running projects and ongoing work as well as contributions from industry. Papers that investigate multiple themes directly are especially welcome.

=== Submission Details ===
All submissions must be written in English following Springer LNCS author guidelines (max. 6 pages for short and 12 pages for full papers, Springer LNCS: <http://www.springer.com/lncs>; exclusive of unlimited pages for references) 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.

EasyChair: <https://easychair.org/conferences/?conf=birndl2016>

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

Planned IJDL Special Issue:
We are currently working with the International Journal on Digital Libraries (IJDL) to edit a special issue that may feature extended works from BIRNDL.  Selected workshop papers from BIRNDL may be fast-tracked for extension shortly after the workshop, and be re-reviewed for publication.  IJDL is a Springer journal and indexed in SCOPUS, INSPEC, ACM Digital Library, DBLP, and other indices.


=== Organizers ===
Guillaume Cabanac, University of Toulouse, France
Muthu Kumar Chandrasekaran, School of Computing, National University of Singapore, Singapore
Ingo Frommholz, University of Bedfordshire in Luton, UK
Kokil Jaidka, Big Data Experience Lab, Adobe Research, India
Min-Yen Kan, School of Computing, National University of Singapore, Singapore
Philipp Mayr, GESIS - Leibniz Institute for the Social Sciences, Germany
Dietmar Wolfram, School of Information Studies, University of Wisconsin-Milwaukee, USA

=== Program Committee ===
Akiko Aizawa, National Institute of Informatics, Japan
Iana Atanassova, Université de Franche-Comté, France
Joeran Beel, University of Konstanz, Germany
Patrice Bellot, Aix-Marseille University, France
Marc Bertin, Université du Québec à Montréal, Canada
Colin Batchelor, Royal Society of Chemistry, Cambridge, UK
Cornelia Caragea, University of North Texas
Zeljko Carevic, GESIS, Germany
Jason S Chang, National Tsing Hua University, Taiwan
John Conroy, IDA Center for Computing Sciences
Ed A. Fox, Virginia Tech, USA
C. Lee Giles, Penn State University
Bela Gipp, University of Konstanz, Germany
Nazli Goharian, Georgetown University
Sujatha Das Gollapalli, Institute for Infocomm Research, A*STAR, Singapore
Pawan Goyal, Indian Institute of Technology, Kharagpur
Daniel Hienert, GESIS, Germany
Gilles Hubert, University of Toulouse, France
Rahul Jha, Microsoft
Noriko Kando, National Institute of Informatics, Japan
Dain Kaplan, Tokyo Institute of Technology
Roman Kern, Graz University of Technology
Claus-Peter Klas, GESIS, Germany
Anna Korhonen, University of Cambridge
John Lawrence, University of Dundee
Cyril Labbé, Université Joseph Fourier, Grenoble, France
Birger Larsen, Aalborg University, Denmark
Elizabeth Liddy, Syracuse University
Chin-Yew Lin, Microsoft Research
Xiaozhong Liu, Indiana University, Bloomington
Kathy McKeown, Columbia University
Stasa Milojevic, Indiana University, USA
Prasenjit Mitra, Penn State University / Qatar Computing Research Institute
Marie-Francine Moens, KU Leuven
Peter Mutschke, GESIS, Germany
Preslav Nakov, Qatar Computing Research Institute
Doug Oard, University of Maryland, College Park
Manabu Okumura, Tokyo Institute of Technology
Byung-won On, Kunsan National University
Arzucan Ozgur, Bogazici University
Cecile Paris, The Commonwealth Scientific and Industrial Research Organisation
Philipp Schaer, GESIS, Germany
Andrea Scharnhorst, DANS, Netherlands
Henry Small, SciTech Strategies, USA
Kazunari Sugiyama, National University of Singapore
Simone Teufel, University of Cambridge
Mike Thelwall, University of Wolverhampton
Lucy Vanderwende, Microsoft Research
Vasudeva Varma, International Institute of Information Technology, Hyderabad, India
Andre Vellino, University of Toronto
Anita de Waard, Elsevier Labs
Alex Wade, Microsoft Research
Stephen Wan, CSIRO ICT Centre, Australia

--
Dr. Philipp Mayr
Team Leader

GESIS - Leibniz Institute for the Social Sciences
Unter Sachsenhausen 6-8,  D-50667 Köln, Germany
Tel: + 49 (0) 221 / 476 94 -533
Email: philipp.mayr at gesis.org
Web: http://www.gesis.org

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