[InetBib] [CfP] Joint workshop on Bibliometric-enhanced IR and NLP for Digital Libraries (BIRNDL) @ SIGIR 2019

["Mayr-Schlegel, Philipp via InetBib" <inetbib@xxxxxxxxxx>]

=== Call for Papers ===

You are invited to participate in the 4th Joint Workshop on 
Bibliometric-enhanced IR and NLP for Digital Libraries (BIRNDL), to be held as 
part of 42nd International ACM SIGIR Conference on Research and Development in 
Information Retrieval (SIGIR 2019) in Paris, France on 25th July 2019.

<http://wing.comp.nus.edu.sg/~birndl2019/>.



This is the 4th BIRNDL workshop, third at SIGIR, following a series of 
successful BIR workshops at ECIR and other premier IR venues. In conjunction 
with the BIRNDL workshop, we will also hold the 5th CL-SciSumm Shared Task in 
Scientific Document Summarization. 
<http://wing.comp.nus.edu.sg/~cl-scisumm2019>.

BIRNDL is sponsored by SRI International<http://www.sri.com/> and 
Chan-Zuckerberg Initiative<https://chanzuckerberg.com/>.



=== Important Dates ===

- Submissions deadline: May 3, 2019

- Notification: May 31, 2019

- Camera Ready Contributions: July 7, 2019

- Workshop: July 25, 2019 in Paris, France

=== Aim of the Workshop ===

The goal of the BIRNDL workshop at SIGIR 2019 is to engage the IR community in 
the open problems in Big Science. Big Science refers to the large, cross-domain 
digital repositories which index research papers, such as the ACL Anthology, 
ArXiv, ACM Digital Library, PubMed, IEEE database, Web of Science and Google 
Scholar. Currently, digital libraries collect and allow access to digital 
papers and their metadata---inclusive of citations---but mostly do not analyze 
the items they index. The scale of growth in scholarly publishing poses a 
challenge for scholars in their search for relevant literature. Finding 
relevant scholarly literature is the key focus of the workshop and sets the 
agenda for methods and approaches to be discussed and evaluated at BIRNDL.



We invite papers that draw on insights from IR, bibliometrics and NLP to 
develop new methods to open problems in Big Science, such as evidence-based 
searching, measurement of research quality, relevance and impact, the emergence 
and decline of research problems, identification of scholarly relationships and 
influences and applied problems such as language translation, 
question-answering and summarization.



For your reference: Proceedings of the third BIRNDL workshop at SIGIR 2018 
<http://ceur-ws.org/Vol-2132/>and a recent report in SIGIR Forum 
<http://sigir.org/wp-content/uploads/2019/01/p105.pdf>.



=== Workshop Topics ===

By design, BIRNDL is an inclusive and diverse venue, in terms of both 
constituency and research. To promote a diverse constituency, we explicitly 
encourage female first authors. We invite stimulating research on topics 
including, but not limited to, full-text analysis, including multilingual 
analysis, IR methods for DL, and applications of citation-based NLP. Specific 
examples of fields of interest include



- Infrastructure for scientific mining and IR,

- Semantic and Network-based indexing, navigation, searching and browsing in 
structured data,

- Discourse structure identification and argument mining from scientific papers,

- Summarisation and question-answering for scholarly DLs,

- Bibliometrics, citation analysis and network analysis for IR,

- Recommendation for scholarly papers, reviewers, citations and publication 
venues,

- Measurement and evaluation of quality and impact,

- Information extraction and parsing tasks in scientific papers,

- Science knowledge base population (Sci-KBP) and inference,

- Automated discovery and maintenance of metadata and controlled vocabularies,
- Disambiguation issues in scholarly DLs.

Importantly, to address the scarcity of validated datasets in this area, we 
also invite papers describing new and pre-existing datasets. Submissions in 
this track will include instructions for accessing the data; metadata and 
documentation on its organization, content, and quality; and descriptions of 
possible use cases. We also invite descriptions of running projects and ongoing 
work as well as contributions from industry. Papers that investigate multiple 
themes are welcome.



=== The CL-SciSumm Shared Task ===

CL-SciSumm19 is expected to be of interest to a broad community including those 
working in computational linguistics and natural language processing, text 
summarization, discourse structure in scholarly discourse, paraphrase, textual 
entailment and text simplification. The task constitutes automatic scientific 
paper summarization in the Computational Linguistics (CL) domain. The output 
summaries will be of two types: faceted summaries of the traditional 
self-summary (the abstract) and the community summary (the collection of 
citation sentences ‘citances’). We also propose to group the citances by the 
facets of the text that they refer to.

At SIGIR 2019, we will hold the 5th Computational Linguistics (CL) Scientific 
Summarization Shared Task http://wing.comp.nus.edu.sg/~cl-scisumm2019 which is 
sponsored by SRI International and Chan-Zuckerberg Initiative (CZI). This task 
follows up on the successful CL-SciSumm-2018 @ SIGIR 2018 and three previous 
editions. In this task, a training corpus of 40 manually annotated topics and 
1000 auto-annotated from CL research papers are released. Participants are 
invited to enter their systems in a task-based evaluation on a blind test set.



=== Submission Information ===

- Main track: All submissions must be written in English, following the 
Springer LNCS author guidelines (max. 6 pages for short and 12 pages for full 
papers; exclusive of unlimited pages for references) and should be submitted as 
PDF files to EasyChair <https://easychair.org/conferences/?conf=birndl2019>. 
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 submissions and reviewing will be managed by the EasyChair conference 
management system.

- Poster track: We welcome submissions detailing original, early findings, 
works in progress and industrial applications of bibliometrics and IR for a 
special poster session, possibly with a 2-minute presentation in the main 
session. Some research track papers will also be invited to the poster track 
instead, although there will be no difference in the final proceedings between 
poster and research track submissions. These papers should follow the same 
format as the research track papers.

- The CL-SciSumm Shared Task: Teams that wish to participate in the CL Shared 
Task track at BIRNDL 2019 are invited to register on EasyChair with a title and 
a tentative abstract describing their approach at

<https://easychair.org/conferences/?conf=clscisumm2019>. Participants are 
advised to register as soon as possible in order to receive timely access to 
evaluation resources, including development and testing data. Registration for 
the task does not commit you to participation - but is helpful to know for 
planning. All participants who submit system runs are welcome to present their 
system at the BIRNDL Workshop in the poster session, while the best performing 
system will be invited to present their paper in the main session. 
Dissemination of CL-SciSumm work and results other than in the workshop 
proceedings is welcomed, but the conditions of participation specifically 
preclude any advertising claims based on these results. Any questions about 
conference participation may be sent to the organizers mentioned below.



=== Main Organising Committee ===

- Muthu Kumar Chandrasekaran <https://www.linkedin.com/in/muthukumarc87/>

- Philipp Mayr <https://philippmayr.github.io/>

- Dayne Freitag <https://www.sri.com/about/people/dayne-freitag>

- Kokil Jaidka <http://kokiljaidka.wordpress.com/>

- Min-Yen Kan <https://www.comp.nus.edu.sg/~kanmy/>



The main committee also has the support of the past organisers: Guillaume 
Cabanac, Ingo Fromholz, Dietmar Wolfram.

Thanks!
Muthu (Co-organiser, BIRNDL)

Muthu Kumar Chandrasekaran
Advanced Computer Scientist, Machine Learning
​Artificial Intelligence Center (AIC), ​SRI International
333, Ravenswood Ave, Menlo Park, CA

LinkedIn <https://linkedin.com/in/cmkumar/> | Google Scholar 
Profile<https://scholar.google.com/citations?user=TNXPTz0AAAAJ&hl=en>