|
The topics of the workshop will be organised around the following themes:
- The whole ecosystem of infrastructures including repositories, aggregators, text-and data-mining facilities, impact monitoring tools, datasets, services and APIs that enable analysis of large volumes of scientific publications.
- Semantic enrichment of scientific publications by means of text and data mining.
- Analysis of large databases of scientific publications to identify research trends, high impact and improve access to research content.
Topics of interest relevant to theme 1 include but are not limited to:
- Infrastructures including repositories, aggregators, text-and data-mining facilities, impact monitoring tools, datasets, services and APIs for accessing scientific publications and/or research data. The existence of datasets, services, systems and APIs (in particular those that are open) providing access to large volumes of scientific publications and research data, is an essential prerequisite for being able to research and develop new technologies that can transform the way people do research. We invite papers presenting innovative approaches to the development of these systems that enable people to access databases and carry out their analysis. Papers addressing Open Access are of special interest. We also welcome submissions discussing the technical aspects of supporting Open Science, in particular reproducibility of research, sharing of scientific workflows and linking research data with publications. Finally, we also invite papers discussing issues and current challenges in the design of these systems.
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 the aspect 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 a special interest.
- Semantically enriching/annotating publications by crowdsourcingCrowdsourcing 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, (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, other relevant crowdsourcing topics relevant to the domain of scientific publications.
Topics of interest relevant to theme 3 include but are not limited to:
- New methods, models and innovative approaches for measuring impact of publications. The most widely used metrics for measuring impact are based on citations. However, counting citations not taking into account the publication content and the qualitative nature of the citation. In addition, there is a delay between the publication and the measurable impact in citations. We in particular encourage papers addressing new ways of using textual resources for evaluating publications’ importance, such as based on the ideas of detecting (textual) novelty/contribution of works or automatic classification of citation types, sentiment or influence.
- New methods for measuring performance of researchers or research groups. Methods for assessing impact of a publication can be often extended to methods that can assess the impact of individual researchers. However, there are also other criteria for measuring impact in addition to publications, such as the development and publication of research data, economical and market impact that should also be taken into account. We welcome papers addressing these aspects.
- Methods for identifying research trends and cross-fertilization between research disciplines. Identifying research trends should allow discovering newly emerging disciplines or it should help to explain why certain fields are attracting the attention of a wider research community. Such monitoring is important for research funders and governments in order to be able to quickly respond to new developments. We invite papers discussing new methods for identifying trends and cross-fertilization between research disciplines using methods ranging from social network analysis and text- and data-mining to innovative visualization approaches.
- Applications and case studies of mining from scientific databases and publications. New methods and models developed for mining from scientific publications can be applied in many different scenarios, such as improving access to scientific publications, providing exploratory search in digital collections, identifying experts. We encourage papers describing innovative approaches that use scientific publications and data to solve real-world (discipline-specific) problems.
- Exploratory search and Recommender systems for research.This topic addresses research carried out to improve access to very large collections of research publications to improve the way research process is conducted.
|
