[CfP] 1st International Workshop on Approaches for Making Data Interoperable (AMAR 2019)

Call For Papers

1st International Workshop on Approaches for Making Data Interoperable
(AMAR 2019)

https://events.tib.eu/amar2019/
co-located with SEMANTiCS 2019

September 09 – 12, 2019 Karlsruhe, Germany

Submission deadline: July 9, 2019

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Overview

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Recently, there has been a rapid growth in the amount of data available on
the Web. Data is produced by different communities working in a wide range
of domains, using several techniques. This way a large volume of data in
different formats and languages is generated. Accessibility of such
heterogeneous and multilingual data becomes an obstacle for reuse due to
the incompatibility of data formats and the language gap. This
incompatibility of data formats impedes the accessibility of data sources
to the right community. For instance, most of open domain question
answering systems are developed to be effective when data is represented in
RDF. They can not operate with data in the very common CSV files or
presented in unstructured formats. Usually, the data they draw from is in
English rendering them unable to answer questions e.g. in Spanish. On the
other hand, NLP applications in Spanish cannot make use of a knowledge
graph in English. Different communities have different requirements in
terms of data representation and modeling. It is crucial to make the data
interoperable to make it accessible for a variety of applications.

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Topics of Interest

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We invite paper submissions from two communities: (i) data consumers and
(ii) data providers. This includes practitioners, such as data scientists,
that have experience in fitting the data available to their use case;
Semantic Web researchers, that have been investigating data reuse from
heterogeneous data in tools; researchers in the field of data linking and
translation; and other researchers working on the general field of data
integration.

We invite submissions from the following communities:

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   Data Integration
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   Multilingual Data
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   Data Linking
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   Ontology and Knowledge Engineering

We welcome original contributions about all topics related to data
interoperability, including but not limited to:

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   Approaches to convert data between formats, languages, and schema
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   Best practices for processing heterogeneous data
   -

   Translation of different language data
   -

   Cross-lingual applications
   -

   Recommendations for language modeling in linked data
   -

   Labeling of data with natural language information
   -

   Datasets for different communities’ data needs
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   Tools reusing different data formats
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   Converting datasets between different formats
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   Applications in different domains, e.g., Life Sciences, Scholarly,
   Industry 4.0, Humanities

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Author Instructions
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Paper submission this workshop will be via EasyChair (
https://easychair.org/conferences/?conf=amar2019). The papers should follow
the Springer LNCS format, and be submitted in PDF on or before July 9, 2019
(midnight Hawaii time).

We accept papers of the following formats:

   -

   Full research papers (8 - 12 pages)
   -

   Short research papers (3 - 5 pages)
   -

   Position papers (6 - 8 pages)
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   Resource papers (8 - 12 pages, including the publication of the dataset)
   -

   In-Use papers (6 - 8 pages)

Accepted papers will be published as CEUR workshop proceedings. We target
the creation of a special issue including the best papers of the workshop.

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Important Dates
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Submission: July 9, 2019
Notification: July 30, 2019
Workshop: September 9, 2019

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Workshop Organizers
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Lucie-Aimée Kaffee, University of Southampton, UK & TIB Leibniz Information
Centre for Science and Technology, Hannover, Germany
Kemele M. Endris, TIB Leibniz Information Centre for Science and Technology
and L3S Research Centre University of Hannover, Germany
Maria-Esther Vidal, TIB Leibniz Information Centre for Science and
Technology and and L3S Research Centre University of Hannover, Germany

Please contact us, if you have any questions

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Program Committee
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Jeremy Debattista, Trinity College Dublin

Irlan Grangel, Bosch Corporate Research

Lydia Pintscher, Wikimedia Deutschland (Wikidata)

Alokkumar Jha, Insight Centre for Data Analytics

Amrapali Zaveri, Maastricht University

Maribel Acosta, Karlsruhe Institute of Technology

Manolis Koubarakis, National and Kapodistrian University of Athens

Elena Montiel Ponsoda, Universidad Politécnica de Madrid

Javier D. Fernández, Vienna University of Economics and Business

Diego Collarana, Enterprise Information System (EIS)

Elena Demidova, L3S Research Center

David Chaves Fraga, Universidad Politécnica de Madrid

Jose M. Gimenez Garcia, Universite Jean-Monnet

Julia Bosque Gil, Universidad Politécnica de Madrid


-- 
Lucie-Aimée Kaffee
Web and Internet Science Group
School of Electronics and Computer Science
University of Southampton