Thursday, June 8, 2017

CFP: Special Issue on Managing the Evolution and Preservation of the Data Web

Special Issue of the JWS on MEPDaW

The Journal of Web Semantics invites submissions for a special issue on Managing the Evolution and Preservation of the Data Web to be edited by Jeremy Debattista, Javier D. Fernández, Jürgen Umbrich and Maria-Esther Vidal

EXTENDED DEADLINE:  Submissions are due by 28th September 2017.

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 implications to other datasets linked to it. The distributed, dynamic 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 afford on-going access to continuously assess the quality of such dynamic datasets.

The aim of this special issue is to present latest advances in the area and further attract attention to these issues from interested communities. Providing new techniques and innovative solutions to address challenges portrayed by the ever-growing Web of Data, will foster wider adoption of Semantic technologies within different domains and scenarios that would increase the consumption of Linked Data. More specifically, we expect submissions on (but not restricted to) the following topics.

       Management of Data Versioning
     Representation and maintenance of data versions and changes (change representation, change detection)
     Efficient indexing to resolve time-based queries
     Efficient versioned data access (retrieval, sharing, distribution, streaming)
     Languages to query versioned data stores
     Benchmarking of versioning data stores
       Reasoning of Evolving Knowledge
     Evolving patterns extraction
     Reasoning for trend analysis
     Reasoning for knowledge shift detection
     Exploitation of reasoning results to recommendation systems
       Visualization and Presentation of Evolving Knowledge
     Browsing evolving knowledge
     Visualizing trends
     Visual summarization of knowledge sub-domains
     User interfaces for evolving knowledge presentation
       Data Preservation
     Digital preservation for the Web of Data
     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
     Efficient access of different versions of an ontology
     Concept drift representation
     Detection and prediction

This special issue especially welcomes quality papers from related conference tracks and workshops, such as the Data versioning track[1] of the International Conference on Semantic Systems (SEMANTiCS 2016), the International Workshop on Semantic Change & Evolving Semantics[2] (SuCCESS’16), the Drift-a-LOD Workshop[3]: Detection, Representation and Management of Concept Drift in Linked Open Data, and the Workshop on Managing the Evolution and Preservation of the Data Web[4] (MEPDaW). In particular, invited papers from the MEPDaW workshop will be shepherded by experts in this area.

Important Dates

  • Submission deadline: 28th September 2017
  • Author notification: 30th November 2017
  • Final version: 15th February 2018
  • Final notification: 15th March 2018
  • Publication: 28th March 2018

Guest Editors

[Contact person] Jeremy Debattista (ADAPT Centre, School of Computer Science and Statistics, Trinity College Dublin, Ireland; Email:; Webpage: is a research fellow at the ADAPT Centre in Trinity College Dublin. His PhD topic addressed data quality issues in Linked Data, looking at techniques to efficiently assess large linked datasets and modelling of quality metadata. His research interests are on data quality, Big Data for the Semantic Web, and data management.

Javier D. Fernandez (Vienna University of Economics and Business;; Webpage: holds a PhD in Computer Science by the University of Valladolid (Spain), and the University of Chile (Chile). His thesis addressed efficient management of Big Semantic Data, proposing a binary RDF representation for scalable publishing, exchanging and consumption in the Web of Data. Dr. Javier D. Fernandez is currently 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.

Jürgen Umbrich (Vienna University of Economics and Business; Email:; Webpage: holds a PhD degree from the Digital Enterprise Research Institute at the National University Ireland, Galway since 2012. His PhD topic was centred around efficient SPARQL query processing over evolving RDF data on the Web, partially through lightweight RDFS reasoning and a novel hybrid execution query framework. Dr. Jürgen Umbrich is currently a post-doctoral research at WU Vienna with research interests in (Open) Data quality assessment, monitoring and archiving. 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.

Maria-Esther Vidal (Universidad Simon Bolivar and Fraunhofer- IAIS; Email:; Webpage: is a full professor (on-leave) at Universidad Simón Bolívar (USB) Venezuela and a Research Scientist at the Fraunhofer  Institute for Intelligent Analysis and Information Systems (IAIS). Her interests include data and knowledge management, knowledge representation, big data, and semantic web. Prof. Vidal  has published more than 120 peer-reviewed papers in Semantic Web, Databases, Bioinformatics, and Artificial Intelligence. Prof. Vidal  is part of various editorial boards (e.g., JWS, JDIQ), and has been co-chair, senior member, and reviewer of several scientific events and journals (e.g., ESWC, AAAI, AMW, WWW, KDE). She has been visiting professor in different universities (e.g., UMD, University of Bonn, UPM, UPC, KIT, U. Nantes) and participated in several  international projects in EU and USA.

    Submission Guidelines

    The Journal of Web Semantics solicits original scientific contributions of high quality. Following the overall mission of the journal, we emphasize the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services.

    Submission of your manuscript is welcome provided that it, or any translation of it, has not been copyrighted or published and is not being submitted for publication elsewhere. Manuscripts should be prepared for publication in accordance with instructions given in the JWS guide for authors. The submission and review process will be carried out using Elsevier's Web-based EES system. Upon acceptance of an article, the author(s) will be asked to transfer copyright of the article to the publisher. This transfer will ensure the widest possible dissemination of information. Elsevier's liberal preprint policy permits authors and their institutions to host preprints on their web sites. Preprints of the articles will be made freely accessible on the JWS preprint server. Final copies of accepted publications will appear in print and at Elsevier's archival online server.

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