3rd workshop edition co-located with 14th European Semantic Web Conference 2017 in Portoroz, Slovenia.
- 01/04/2017 - 6 Papers Accepted - Notifications Sent
- 12/03/2017 - 7 Submitted Papers
- 02/03/2017 - Deadline Extension - New Submission Date 12/03/2017
- 18/01/2017 - Twitter Account Online
- 16/01/2017 - Best Paper Award supported by Dydra
- 10/01/2017 - Planning a Special Journal Issue
- 06/12/2016 - Website Online
- 05/12/2016 - Workshop accepted at ESWC2017
- Vânia Vidal, Narciso Arruda Jr, Matheus Cruz, Marco Antonio Casanova, Carlos Eduardo Brito and Valéria Magalhães Pequeno - Computing Changesets for RDF Views of Relational Data
- Narumol Prangnawarat and Conor Hayes - Temporal Evolution of Entity Relatedness using Wikipedia and DBpedia
- Ruben Taelman, Miel Vander Sande, Ruben Verborgh and Erik Mannens - Versioned Triple Pattern Fragments: A Low-cost Linked Data Interface Feature for Web Archives
- Natanael Arndt, Patrick Naumann and Edgard Marx - Exploring the Evolution and Provenance of Git Versioned RDF Data
- Thanos Stavropoulos, Efstratios Kontopoulos, Albert Meroño Peñuela, Stavros Tachos, Stelios Andreadis and Yiannis Kompatsiaris - Cross-domain Semantic Drift Measurement in Ontologies Using the SemaDrift Tool and Metrics
- Melisachew Wudage Chekol, Valeria Fionda and Giuseppe Pirrò - Time Travel Queries in RDF Archives
There is a vast and rapidly increasing quantity of scientific, corporate, government, and crowd-sourced data published on the emerging Data Web. Open Data are expected to play a catalyst role in the way structured information is exploited on a large scale. This offers a great potential for building innovative products and services that create new value from already collected data. It is expected to foster active citizenship (e.g., around the topics of journalism, greenhouse gas emissions, food supply-chains, smart mobility, etc.) and world-wide research according to the “fourth paradigm of science”.
Published datasets are openly available on the Web. A traditional view of digitally preserving them by “pickling them and locking them away” for future use, like groceries, conflicts with their evolution. There are a number of approaches and frameworks, such as the Linked Data Stack, that manage a full life-cycle of the Data Web. More specifically, these techniques are expected to tackle major issues such as the synchronisation problem (how to monitor changes), the curation problem (how to repair data imperfections), the appraisal problem (how to assess the quality of a dataset), the citation problem (how to cite a particular version of a linked dataset), the archiving problem (how to retrieve the most recent or a particular version of a dataset), and the sustainability problem (how to support preservation at scale, ensuring long-term access).
Preserving linked open datasets poses a number of challenges, mainly related to the nature of the Linked Data principles and the RDF data model. Since resources are globally interlinked, effective citation measures are required. Another challenge is to determine the consequences that changes to one LOD dataset may have to other datasets linked to it. The distributed nature of LOD datasets furthermore introduces additional complexity, since external sources that are being linked to may change or become unavailable. Finally, another challenge is to identify means to continuously assess the quality of dynamic datasets.
During last year’s workshop, a number of open research questions were raised during the keynote and discussions:
- How can we represent archives of continuously evolving linked datasets? (efficiency vs. compact representation)
- How can we measure the performance of systems for archiving evolving datasets, in terms of representation, efficiency and compactness?
- How can we improve completeness of archiving?
- How can emerging retrieval demands in archiving (e.g. time-traversing and traceability) be satisfied? What type of data analytics can we perform on top of the archived Web of data?
- How can certain time-specific queries over archives be answered? Can we re-use existing technologies (e.g. SPARQL or temporal extensions)? What is the right query language for such queries?
- Is there an actual and urgent need in the community for handling the dynamicity of the Data Web?
- Is there the need of a killer-app to kick start the management of the evolving Web of Data?
Friday 3rd March 2017Sunday 12th March 2017
- Notification: Friday 31st March 2017
- Final version: Thursday 13th April 2017
- Workshop: 28th May 2017
Topics of Interest
This workshop aims at addressing the above mentioned challenges and issues by providing a forum for researchers and practitioners who apply linked data technologies to discuss, exchange and disseminate their work. More broadly, this forum will enable communities interested in data, knowledge and ontology dynamics to network and cross-fertilise.
Topics of interest include, but are not limited to the following themes related to the evolution and preservation of linked data:
- Management of Data Versioning: Efficient representation and maintenance of data versions, high-level (semantic) change management (change representation, change detection), vertical and horizontal scalable versioning of Knowledge Bases, efficient indexing to resolve time-based queries, languages to query versioned data stores, benchmarking of versioning data stores, efficient versioned data access (retrieval, sharing, distribution, streaming);
- Reasoning of Evolving Knowledge: Evolving patterns extraction, reasoning for trend analysis, reasoning for knowledge shift detection; exploitation of reasoning results to recommendation systems;
- The Visualization and Presentation of Evolving Knowledge: Browsing evolving knowledge, Visualizing trends, changes and paradigm shifts, Visual summarization of knowledge sub-domains, User interfaces for evolving knowledge presentation;
- Data Preservation: Digital preservation for linked data, Digital preservation for the Data Web, Dynamics of context or background (tacit) knowledge, design of evolution-aware Linked Data applications (for appraisal, storage management, interlinking, analysis);
- Data Quality and Provenance: Incremental quality assessment for evolving knowledge, Provenance in evolution;
- Ontology Evolution and Concept Drift: Representation of evolving ontologies, Maven-like access of different versions of an ontology, concept drift representation, detection and prediction.
We envision three types of submissions in order to cover the entire spectrum from mature research papers to novel ideas/datasets and industry technical talks:
- Research Papers (max 15 pages), presenting novel scientific research addressing the topics of the workshop.
- Position Papers, Demo papers and System and Dataset descriptions (max 5 pages), encouraging papers describing significant work in progress, late breaking results or ideas of the domain, as well as functional systems or datasets relevant to the community.
- Industry & Use Case Presentations (max 5 pages), in which industry experts can present and discuss practical solutions, use case prototypes, best practices, etc., in any stage of implementation.
We are also planning to organise a special issue on the concerning the topics of the workshop, encouraging the selected contributions to the workshop to submit and extend their version to this special issue. All papers accepted for this extension will go through the standard journal evaluation process.
Submit your papers through the Easy Chair Link
Last year's proceedings can be found as joint proceedings here
Best Paper Award
Dydra (http://dydra.com/) will sponsor an award for the best research paper submitted. Selection criteria include the innovative nature of work, the importance and timeliness of the topic, and the overall readiness and quality of the writing. We particularly encourage student submissions, which will be given preference.
Javier D. Fernández (Vienna University of Economics and Business; Email:; Webpage [Contact Person] ) is a post-doctoral research fellow under an FWF (Austrian Science funds) Lise-Meitner grant. His current research focuses on efficient management of Big Semantic Data, RDF streaming, archiving and querying dynamic Linked Data.
Jeremy Debattista (Enterprise Information Systems, University of Bonn, Germany and Fraunhofer IAIS, Germany; Webpage) is a PhD researcher at the University of Bonn. His research interests are on Linked Data Quality and Big Data for the Semantic Web.
Jürgen Umbrich (Vienna University of Economics and Business; Webpage) is a post-doctoral research at WU Vienna with research intrests in (Open) Data quality assessment and monitoring and archieving. Before he joined the WU, he worked one year as a post-doctoral researcher at Fujitsu Ireland in Galway exploiting the benefits of Linked Data for enterprise applications.
- James Anderson, Dydra
- Wouter Beek, VU Amsterdam, The Netherlands
- Magnus Knuth, Hasso Plattner Institute, Germany
- Christoph Lange, University of Bonn/Fraunhofer IAIS, Germany
- Axel Polleres, Vienna University of Economics and Business, Austria
- Miel Vander Sande, Ghent University, Belgium
- Maria-Esther Vidal, Universidad Simon Bolivar/Fraunhofer IAIS, Germany
- Natanael Arndt, AKSW, Leipzig, Germany
- Jean-Paul Calbimonte, HES-SO Valais, Switzerland
- Melisachew Wudage Chekol, University of Mannheim, Germany
- Ioannis Chrysakis, FORTH-ICS, Greece
- Valeria Fionda, University of Calabria, Italy
- Giorgos Flouris, FORTH-ICS, Greece
- Steffen Lohmann, Fraunhofer IAIS, Germany
- Michael Martin, AKSW, Leipzig, Germany
- Marios Meimaris, ATHENA R.C., Greece
- Axel-Cyrille Ngonga Ngomo, AKSW, Leipzig, Germany
- George Papastefanatos, ATHENA R.C., Greece
- Giuseppe Pirro, ICAR-CNR, Italy
- Ruben Taelman, Ghent University, Belgium
- Maribel Acosta, Karlsruhe Institute of Technology (KIT), Germany
- Charlie Abela, University of Malta, Malta
If you have any questions related to the workshop, email us