2ND International Workshop on Mining Scientific Publications
May 26, 2013 – Submission deadline
June 23, 2013 – Notification of acceptance
July 7, 2013 – Camera-ready
July 26, 2013 – Workshop
From the CFP:
Digital libraries that store scientific publications are becoming increasingly important in research. They are used not only for traditional tasks such as finding and storing research outputs, but also as sources for mining this information, discovering new research trends and evaluating research excellence. The rapid growth in the number of scientific publications being deposited in digital libraries makes it no longer sufficient to provide access to content to human readers only. It is equally important to allow machines analyse this information and by doing so facilitate the processes by which research is being accomplished. Recent developments in natural language processing, information retrieval, the semantic web and other disciplines make it possible to transform the way we work with scientific publications. However, in order to make this happen, researchers first need to be able to easily access and use large databases of scientific publications and research data, to carry out experiments.
This workshop aims to bring together people from different backgrounds who:
(a) are interested in analysing and mining databases of scientific publications,
(b) develop systems, infrastructures or datasets that enable such analysis and mining,
(c) design novel technologies that improve the way research is being accomplished or
(d) support the openness and free availability of publications and research data.2. TOPICS
The topics of the workshop will be organised around the following three themes:
- Infrastructures, systems, open datasets or APIs that enable analysis of large volumes of scientific publications.
- Semantic enrichment of scientific publications by means of text-mining, crowdsourcing or other methods.
- Analysis of large databases of scientific publications to identify research trends, high impact, cross-fertilisation between disciplines, research excellence and to aid content exploration.
Of particular interest for topic mappers:
Topics of interest relevant to theme 2 include, but are not limited to:
- Novel information extraction and text-mining approaches to semantic enrichment of publications. This might range from mining publication structure, such as title, abstract, authors, citation information etc. to more challenging tasks, such as extracting names of applied methods, research questions (or scientific gaps), identifying parts of the scholarly discourse structure etc.
- Automatic categorization and clustering of scientific publications. Methods that can automatically categorize publications according to an established subject-based classification/taxonomy (such as Library of Congress classification, UNESCO thesaurus, DOAJ subject classification, Library of Congress Subject Headings) are of particular interest. Other approaches might involve automatic clustering or classification of research publications according to various criteria.
- New methods and models for connecting and interlinking scientific publications. Scientific publications in digital libraries are not isolated islands. Connecting publications using explicitly defined citations is very restrictive and has many disadvantages. We are interested in innovative technologies that can automatically connect and interlink publications or parts of publications, according to various criteria, such as semantic similarity, contradiction, argument support or other relationship types.
- Models for semantically representing and annotating publications. This topic is related to aspects of semantically modeling publications and scholarly discourse. Models that are practical with respect to the state-of-the-art in Natural Language Processing (NLP) technologies are of special interest.
- Semantically enriching/annotating publications by crowdsourcing. Crowdsourcing can be used in innovative ways to annotate publications with richer metadata or to approve/disapprove annotations created using text-mining or other approaches. We welcome papers that address the following questions: (a) what incentives should be provided to motivate users in contributing metadata, (b) how to apply crowdsourcing in the specialized domains of scientific publications, (c) what tasks in the domain of organising scientific publications is crowdsourcing suitable for and where it might fail, (d) other relevant crowdsourcing topics relevant to the domain of scientific publications.
The other themes could be viewed through a topic map lens but semantic enrichment seems like a natural.