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[Final CfP] 4th Workshop on Managing the Evolution and Preservation of the Data Web - MEPDaW 2018 @ ESWC2018 - Deadline Extended now 19th March!

From: Jeremy Debattista <jeremy.debattista@adaptcentre.ie>
Date: Fri, 9 Mar 2018 10:46:33 +0000
Message-Id: <B4115AB5-D8B5-4CC8-A8F2-CCB8CB6EA37A@adaptcentre.ie>
To: SW-forum Web <semantic-web@w3.org>
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CALL FOR PAPERS: 4th Workshop on Managing the Evolution and Preservation of the Data Web - MEPDaW 2018

Co-located with 15th ESWC 2018,  Heraklion, Crete, Greece

Extended Deadline Submission: 9th March 2018 19th March 2018
Workshop:  June 3rd or 4th (to be announced) 

Web:  https://mepdaw2018.ai.wu.ac.at/ <https://mepdaw2018.ai.wu.ac.at/>
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== MOTIVATION ==

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, 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 and add value over time), the appraisal problem (how to assess the quality of a dataset), the citation and provenance problem (how to cite a particular version of a linked dataset, how to keep the lineage/provenance of the data), 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).

Managing the evolution and preservation of 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.

== IMPORTANT DATES ==

- Extended Deadline Submission: 9th March 2018 19th March 2018
- Notification: 5th April 2018
- Final version: Wednesday 18th April 2018
- Workshop: June 3rd or 4th (to be announced) 

== 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
* Change patterns and dynamics

- Reasoning of Evolving Knowledge
* Evolving patterns extraction
* Predicting evolving knowledge
* 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)
* Crawling
 
- Data Quality and Provenance: 
* Incremental quality assessment and validation for evolving knowledge
* Quality trends and prediction for changing knowledge
* Automated repair based on historical context or predictions
* Provenance in evolution

- Ontology Evolution and Concept Drift: 
* Representation of evolving ontologies
* Efficient access of different versions of an ontology
* Detection and prediction
* Ontology change impact assessment
* Long lived transactions for knowledge bases


== SUBMISSION GUIDELINES ==

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:

A) Research Papers (max 15 pages), presenting novel scientific research addressing the topics of the workshop.

B) 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.

C) 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.

Papers should be formatted according to the Springer LNCS format (http://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines <http://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines>) in PDF or equivalent in HTML format (strongly encouraged). Authors new to HTML submissions can look into the Research Articles in Simplified HTML (RASH) Framework (https://github.com/essepuntato/rash <https://github.com/essepuntato/rash>) or dokeli (https://github.com/linkeddata/dokieli <https://github.com/linkeddata/dokieli>). HTML articles can be submitted by either providing an URL to their article (in HTML+RDFa, CSS, JavaScript etc.) with supporting files, or an archived zip file including all the material.

All papers should be submitted to https://easychair.org/conferences/?conf=mepdaw2018 <https://easychair.org/conferences/?conf=mepdaw2018>. 

All accepted papers will be published in the CEUR workshop proceedings series.

== BEST PAPER AWARD ==

We will provide 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.

== ORGANIZING COMMITTEE  ==

- Jeremy Debattista (ADAPT Centre, Trinity College Dublin, Ireland)

- Javier D. Fernández (Vienna University of Economics and Business)

- Jürgen Umbrich (Vienna University of Economics and Business)

- Maria-Esther Vidal (Universidad Simon Bolivar and Technische Informationsbibliothek (TIB);


== ADVISORY BOARD  ==

- James Anderson, Dydra 
- Axel Polleres, Vienna University of Economics and Business, Austria  
- Rob Brennan, ADAPT Centre, Trinity College Dublin, Ireland 


== PROGRAM COMMITTEE  ==

- Maribel Acosta, Karlsruhe Institute of Technology (KIT), Germany
- Natanael Arndt, AKSW, Leipzig, Germany
- Ioannis Chrysakis, FORTH-ICS, Greece
- Valeria Fionda, University of Calabria, Italy
- Giorgos Flouris, FORTH-ICS, Greece
- Marios Meimaris, ATHENA R.C., Greece
- George Papastefanatos, ATHENA R.C., Greece
- Ruben Taelman, Ghent University, Belgium
- Harshvardhan J. Pandit, ADAPT Centre, Trinity College Dublin, Ireland
- Steffen Lohmann, Enterprise Information Systems, University of Bonn, Germany

== CONTACT INFORMATION  ==

Email: mepdaw@googlegroups.com <mailto:mepdaw@googlegroups.com> 
Twitter: @mepdaw <https://twitter.com/mepdaw>
Homepage: https://mepdaw2018.ai.wu.ac.at/ <https://mepdaw2018.ai.wu.ac.at/>
Received on Friday, 9 March 2018 10:47:08 UTC

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