2019 Highlights – Awards and grants

Olaf Hartig has received the 2019 10-Years Award of the Semantic Web Science Association. This annual award recognizes a research paper that has become the most influential work of all papers published ten years ago in the respective edition of the International Semantic Web Conference (ISWC). The ISWC 2009 paper for which Olaf has now won the award started a line of research that focuses on evaluating database queries directly over interlinked data on the Web. In this context, Olaf’s paper pioneered the idea to integrate a traversal-based discovery of relevant data sources into the query execution process, and the paper introduced a first concrete approach to implement this idea in a query execution engine. Since its publication, the paper has spawned numerous other scientific work that proposed alternative approaches, established theoretical foundations of queries and query languages in the given context, and combined the ideas with other forms of query processing.

Robin Keskisärkkä, Eva Blomqvist, Leili Lind and Olaf Hartig won the Best Paper Award for their paper “RSP-QL*: Enabling Statement-Level Annotations in RDF Streams” at SEMANTiCS 2019.

Olaf Hartig won a grant from the Swedish Research Council to establish graph database research.

2019 Highlights – Semantic Web group at ISWC 2019

Our group contributed in several ways to ISWC 2019.
Olaf Hartig was PC co-chair and held, together with Ruben Taelman a tutorial on GraphQL. Information about the tutorial is available at https://www.ida.liu.se/research/semanticweb/events/GraphQLTutorialAtISWC2019.shtml.

Patrick Lambrix and Huanyu Li co-organized two tracks in the Ontology Alignment Evaluation Initiative (the Anatomy track and the Interactive track).

Further, the group presented two posters:
Keskisärkkä R, Li H, Cheng S, Carlsson N, Lambrix P, An Ontology for Ice Hockey,

and

Li H, Armiento R, Lambrix P, Extending Ontologies in the Nanotechnology Domain using Topic Models and Formal Topical Concept Analysis on Unstructured Text.

Conducting and reporting on empirical user studies in Semantic Web contexts

Our colleague Catia Pesquita from Lisbon University is presenting a paper, co-authored by Valentina Ivanova and Patrick Lambrix of our group and Steffen Lohmann from Fraunhofer, at EKAW 2018 – 21st International Conference on Knowledge Engineering and Knowledge Management, on a framework to conduct and report on empirical user studies in Semantic Web contexts. As organizers of the VOILA workshops on Visualization and Interaction for Ontologies and Linked Data  at the recent ISWC conferences, we noticed that both the assessment of interactive Semantic Web approaches as well as the reporting on conducted user studies still suffer from weaknesses.
Empirical evaluations are essential to compare different approaches, demonstrate their benefits and reveal their drawbacks, and thus to facilitate further adoption of Semantic Web technologies. In our paper, we review empirical user studies of user interfaces, visualizations and interaction techniques recently published at several Semantic Web venues, assessing both the user studies themselves and their reporting. We then chart the design space of available methods for user studies in Semantic Web contexts. Finally, we propose a framework for their comprehensive reporting, taking into consideration user expertise, experimental setup, task design, experimental procedures and results analysis.

The original publication is at doi. A self-archived postprint version of the article is available at Linköping University Institutional Repository (DiVA).

Valentina Ivanova defended her PhD thesis on Fostering User Involvement in Ontology Alignment and Alignment Evaluation

On January 26, our PhD candidate Valentina Ivanova defended successfully her thesis with the title “Fostering User Involvement in Ontology Alignment and Alignment Evaluation.”
This thesis focuses on supporting users during the cognitively intensive ontology alignment process and makes several contributions.

First, front- and back-end system features that foster user involvement during the alignment process were identified and their support has been investigated in existing systems Then this was further narrowed down to investigate features in connection to manual validation while also considering the level of user expertise by assessing the impact of user errors on alignments’ quality. As developing and aligning ontologies is an error-prone task, there is also an investigation on the benefits of the integration of ontology alignment and debugging.
Further, interactive comparative exploration and evaluation of multiple alignments at different levels of detail was enabled by developing a dedicated visual environment—Alignment Cubes—which allows for alignments’ evaluation even in the absence of reference alignments.
Finally, inspired by the latest technological advances three promising directions for the application of large, high-resolution displays in the field were identified: improving the navigation in the ontologies and their alignments, supporting reasoning and collaboration between users.

Valentina’s work on the thesis was supervised by Patrick Lambrix, and co-supervised by Nahid Shahmehri. The opponent was Fabien Gandon from INRIA, France. The examination committee consisted of Oscar Corcho from Universidad Politecnica de Madrid, Mathieu d’ Aquin from the National University of Ireland Galway and Claes Lundström from Sectra and Linköping University. Mattias Arvola from Linköping University was backup examination committee member.

Find the thesis in the Diva portal.

LiU Semantic Web research in Semantic Web Special issue on ontology and linked data matching

Two papers with co-authors from our group are published in a special issue on ontology and linked data matching of the Semantic Web journal:

Lambrix P, Kaliyaperumal R, A Session-based Ontology Alignment Approach enabling User Involvement, Semantic Web Journal, 8(2):225-251, 2017.

Zhang Z, Gentile A, Blomqvist E, Augenstein I, Ciravegna F, An unsupervised data-driven method to discover equivalent relations in large Linked Datasets, Semantic Web Journal, 8(2):197-223, 2017.