[AISWorld] [CfP] Extended Deadline: 3rd Workshop on Managing the Evolution and Preservation of the Data Web - MEPDaW 2017, colocated with ESWC2017

[Javier D. Fernández]

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CALL FOR PAPERS: 3rd Workshop on Managing the Evolution and Preservation 
of the Data Web - MEPDaW 2017


Co-located with 14th ESWC 2017,  Portorož, Slovenia


** EXTENDED DEADLINE 12th March 2017 **

Workshop: 28 May 2017


Web: http://eis.iai.uni-bonn.de/Event/mepdaw2017.html
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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”[1].

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[2], 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.


== IMPORTANT DATES ==

- Submission: 12th March 2017 --23:59 Hawaii Time (extended)
- Notification: 31st March 2017
- Final version: Thursday 13th April 2017
- Workshop: 28 May 2017


== 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

Ideally, the proposed solutions should be applicable at web scale.


== 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) 
in PDF or equivalent in HTML format. Authors new to HTML submissions can 
look into the Research Articles in Simplified HTML (RASH) Framework 
(https://github.com/essepuntato/rash) or dokeli 
(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=mepdaw2017.

All accepted papers will be published in the CEUR workshop proceedings 
series. We are also planning to organise a special issue in the 
**Journal of Web Semantics** (under approval) 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.


== 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.


== ORGANIZING COMMITTEE  ==

- Jeremy Debattista (Enterprise Information Systems, University of Bonn, 
Germany / Organized Knowledge, Fraunhofer IAIS, Germany)

- Jürgen Umbrich (Vienna University of Economics and Business)

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


== ADVISORY BOARD  ==

- 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


== PROGRAM COMMITTEE  ==

- Charlie Abela, University of Malta, Malta
- Maribel Acosta, Karlsruhe Institute of Technology (KIT), Germany
- Natanael Arndt, AKSW, Leipzig, Germany -  Confirmed
- 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


== CONTACT INFORMATION  ==

Email: mepdaw at googlegroups.com
Twitter: @mepdaw

Homepage: http://eis.iai.uni-bonn.de/Event/mepdaw2017.html

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[1] T. Hey, S. Tansley, K. Tolle (editors). The Fourth Paradigm: 
Data-Intensive Scientific Discovery. Microsoft Research. 2009.
[2] http://stack.linkeddata.org/