Paper accepted at TPDL 2018

TPDLWe are very pleased to announce that our group got two papers accepted in TPDL 2018 : The 22nd International Conference on Theory and Practice of Digital Libraries.

The TPDL is is a well-established scientific and technical forum on the broad topic of digital libraries, bringing together researchers, developers, content providers and users in digital libraries and digital content management. The 22nd TPDL will take place in Porto, Portugal on September 10-13, 2018. The general theme of TPDL 2018 is “Digital Libraries for Open Knowledge”. 2017-2018 are considered “Year of Open” and 2018 is “the TPDL of Open”. TPDL 2018 wants to gather all the communities engaged to make the knowledge more and more open, using the available technologies, standards and infrastructures, but reflecting about the new challenges, policies and other issues to make it happen. Thus, our activities in the context of scholarly communication matched very well.  

Here is the list of the accepted papers with their abstract: 

  • “Unveiling Scholarly Communities over Knowledge Graphs” by Sahar Vahdati, Guillermo Palma, Rahul Jyoti Nath, Maria-Esther Vidal, Christoph Lange and Sören Auer

    Abstract: Knowledge graphs represent the meaning of properties of real-world entities and relationships among them in a natural way.  Exploiting semantics encoded in knowledge graphs enables the implementation of knowledge-driven tasks such as semantic retrieval, query processing, and question answering, as well as solutions to knowledge discovery tasks including pattern discovery and link prediction.  In this paper, we tackle the problem of knowledge discovery in scholarly knowledge graphs, i.e., graphs that integrate scholarly data, and present KORONA, a knowledge-driven framework able to unveil scholarly communities for the prediction of scholarly networks. \koronaB implements a graph partition approach and relies on semantic similarity measures to determine relatedness between scholarly entities. As a proof of concept, we built a scholarly knowledge graph with data from researchers, conferences, and papers of the Semantic Web area, and apply \koronaB to uncover co-authorship networks. Results observed from our empirical evaluation suggest that exploiting semantics in scholarly knowledge graphs enables the identification of previously unknown relations between researchers. We furthermore point out how these observations can be generalized to other scholarly entities, e.g., articles or institutions, for the prediction of other scholarly patterns, e.g., co-citations or academic collaboration.

  • Metadata Analysis of Scholarly Events on of Computer Science, Physics, Engineering and Mathematicsby Said Fathalla, Sahar Vahdati, Sören Auer and Christoph Lange

    Abstract: Although digitization has significantly eased publishing, finding a relevant and suitable channel of publishing still remains challenging. To obtain a better understanding of scholarly communication in different fields and the role of scientific events, metadata of scientific events of four research communities have analyzed: Computer Science, Physics, Engineering, and Mathematics. Our transferable analysis methodology is based on descriptive statistics as well as exploratory data analysis. Metadata used in this work have been collected from the community platform and SCImago as the main resources containing metadata of scientific events in a semantically structured way. The evaluation uses metrics such as continuity, geographical and time-wise distribution, field popularity and productivity as well as event progress ratio and rankings based on the SJR indicator and h5 indices.

Looking forward to seeing you at The TPDL 2018.