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ACM/IEEE Joint Conference on Digital Libraries 2017
University of Toronto
JCDL 2017 | #JCDL@2017
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Thursday, June 22 • 09:00 - 10:30
Paper Session 10: Scientific Collections and Libraries

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Abdussalam Alawini, Leshang Chen, Susan Davidson and Gianmaria Silvello. Automating data citation: the eagle-i experience (Full)
Data citation is of growing concern for owners of curated databases, who wish to give credit to the contributors and curators responsible for portions of the dataset and enable the data retrieved by a query to be later examined. While several databases specify how data should be cited, they leave it to users to manually construct the citations and do not generate them automatically. 

We report our experiences in automating data citation for an RDF dataset called eagle-i, and discuss how to generalize this to a citation framework that can work across a variety of different types of databases (e.g. relational, XML, and RDF). We also describe how a database administrator would use this framework to automate citation for a particular dataset. 

Sandipan Sikdar, Matteo Marsili, Niloy Ganguly and Animesh Mukherjee. Influence of Reviewer Interaction Network on Long-term Citations: A Case Study of the Scientific Peer-Review System of the Journal of High Energy Physics (Full)

*Best Student Paper Award Nominee

A `peer-review system' in the context of judging research contributions, is one of the prime steps undertaken to ensure the qualityof the submissions received; a significant portion of the publishing budget is spent towards successful completion of the peer-review by the publication houses. Nevertheless, the scientific community is largely reaching a consensus that peer-review system, although indispensable, is nonetheless flawed. 

A very pertinent question therefore is ``could this system be improved?". In this paper, we attempt to present an answer to this question by considering a massive dataset of around $29k$ papers with roughly $70k$ distinct review reports together consisting of $12m$ lines of review text from the Journal of High Energy Physics (JHEP) from 1997 to 2015. In specific, we introduce a novel reviewer-reviewer interaction network (an edge exists between two reviewers if they were assigned by the same editor) and show that surprisingly the simple structural properties of this network such as degree, clustering coefficient, centrality (closeness, betweenness etc.) serve as strong predictors of the long-term citations (i.e., the overall scientific impact) of a submitted paper. Compared to a set of baseline features built from the basic characteristics of the submitted papers, the authors and the referees (e.g., the popularity of the submitting author, the acceptance rate history of a referee, the linguistic properties laden in the text of the review reports etc.), the network features perform manifolds better. Although we do not claim to provide a full-fledged reviewer recommendation system (that could potentially replace an editor), our method could be extremely useful in assisting the editors in deciding the acceptance or rejection of a paper, thereby, improving the effectiveness of the peer-review system.

Martin Klein and Herbert Van De Sompel. Discovering Scholarly Orphans Using ORCID (Full)
Archival efforts such as (C)LOCKSS and Portico are in place to ensure the longevity of traditional scholarly resources like journal articles. At the same time, researchers are depositing a broad variety of other scholarly artifacts into emerging online portals that are designed to support web-based scholarship. These web-native scholarly objects are largely neglected by current archival practices and hence they become scholarly orphans. We therefore argue for a novel paradigm that is tailored towards archiving these scholarly orphans. We are investigating the feasibility of using Open Researcher and Contributor ID (ORCID) as a supporting infrastructure for the process of discovery of web identities and scholarly orphans for active researchers. We analyze ORCID in terms of coverage of researchers, subjects, and location and assess the richness of its profiles in terms of web identities and scholarly artifacts. We find that ORCID currently lacks in all considered aspects and hence can only be considered in conjunction with other discovery sources. However, ORCID is growing fast so there is potential that it could achieve a satisfactory level of coverage and richness in the near future.


Susan Davidson

University of Pennsylvania
avatar for Martin Klein

Martin Klein

Scientist, Los Alamos National Laboratory

Sandipan Sikdar

Indian Institute of Technology Kharagpur
avatar for Gianmaria Silvello

Gianmaria Silvello

Researcher, University of Padua
Data Citation

Herbert Van De Sompel

Scientist, Los Alamos National Laboratory
Herbert Van de Sompel graduated in Mathematics and Computer Science at Ghent University (Belgium), and in 2000 obtained a Ph.D. in Communication Science there. For many years, he headed Library Automation at Ghent University. After leaving Ghent in 2000, he was Visiting Professor in Computer Science at Cornell University, and Director of e-Strategy and Programmes at the British Library. | Currently, he is the team leader of the Prototyping Team at the Research Library of the Los Alamos National Laboratory. The Team does research regarding various aspects of scholarly communication in the digital age, including information infrastructure, interoperability, digital preservation and indicators for the assessment of the quality of units of scholarly communication. Herbert has played a major role in creating the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH), the Open Archives Initiative Object Reuse... Read More →

Thursday June 22, 2017 09:00 - 10:30
Room 325, Faculty of Information 140 St. George Street, Toronto, ON, M5S 3G6

Attendees (16)