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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
Submission (extended&final): 19th March 2018
Workshop: June 3rd or 4th (to be announced)
Web:
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 ==
- Submission (extended&final): 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)
in PDF or equivalent in HTML format (encouraged). 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=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
Twitter: @mepdaw
Homepage:
https://mepdaw2018.ai.wu.ac.at/
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