Paper accepted at iiWAS 2019

We are very happy to announce that our group got one paper accepted at iiWAS 2019: The 21st International Conference on Information Integration and Web-based Applications & Services, which will be held on December 2 – 4 in Munich, Germany.

The 21st International Conference on Information Integration and Web-based Applications & Services (iiWAS2019) is a leading international conference for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all information integration and web-based applications & services related areas.

iiWAS2019 is endorsed by the International Organization for Information Integration and Web-based Applications & Services (@WAS), and will be held from 2-4 December 2019, in Munich, Germany, the city of innovation, technology, art and culture in conjunction with the 17th International Conference on Advances in Mobile Computing & Multimedia (MoMM2019).

Here is the pre-print of the accepted paper with its abstract: 

  • Uniform Access to Multiform Data Lakes using Semantic Technologies” by Mohamed Nadjib Mami, Damien Graux, Simon Scerri, Hajira Jabeen, Sören Auer, and Jens Lehmann.
  • Abstract:  Increasing data volumes have extensively increased application possibilities. However, accessing this data in an ad hoc manner remains an unsolved problem due to the diversity of data management approaches, formats and storage frameworks, resulting in the need to effectively access and process distributed heterogeneous data at scale. For years, Semantic Web techniques have addressed data integration challenges with practical knowledge representation models and ontology-based mappings. Leveraging these techniques, we provide a solution enabling uniform access to large, heterogeneous data sources, without enforcing centralization; thus realizing the vision of a Semantic Data Lake. In this paper, we define the core concepts underlying this vision and the architectural requirements that systems implementing it need to fulfill. Squerall, an example of such a system, is an extensible framework built on top of state-of-the-art Big Data technologies. We focus on Squerall’s distributed query execution techniques and strategies, empirically evaluating its performance throughout its various sub-phases.

Acknowledgement
This work is partly supported by the EU H2020 projects BETTER (GA 776280) and QualiChain (GA 822404), and by the ADAPT Centre for Digital Content Technology funded under the SFI Research Centres Programme (Grant 13/RC/2106) and co-funded under the European Regional Development Fund.


Looking forward to seeing you at The iiWAS 2019.