[CfP] DEADLINE EXTENSION: QEKGraph@K-CAP2017 workshop: submissions now due September 29

* Apologies for cross-posting *

The workshop on Quality Engineering Meets Knowledge Graph (QEKGraph 2017 -
co-located with K-CAP 2017 conference) has slightly extended its submission
deadline. The new deadline is now Friday, September 29. It will be possible
to update submitted papers until Sunday, October 1.

Please consider submitting a contribution to QEKGraph and circulate the
updated call for papers to whoever might be interested.

Many Thanks

==== Call for Papers (QEKGraph 2017) ====
1st International Workshop on Quality Engineering Meets Knowledge Graph-
QEKGraph 2017

Date: December 4, 2017 (TBC)
Venue: Austin, Texas, United States (co-located with K-CAP 2017)
Twitter: @qekgraph
Site: http://qekgraph.kmi.open.ac.uk/index.html

Workshop chairs:
- Shuangyan Liu - The Open University
- Alessandro Adamou - The Open University
- Nandana Mihindukulasooriya - Universidad Politécnica de Madrid

# DESCRIPTION
A knowledge graph is any graph-based knowledge base, which represents a
large network of entities, their semantic types (e.g. a Person or an
Organisation), properties (e.g. the name and birth date of a person), and
relationships between entities such as a person working in an organisation.
Academic research communities, as well as industrial stakeholders, have
constructed a number of large-scale knowledge graphs in recent years such
as DBpedia, YAGO, Freebase, Wikidata, Google Knowledge Graph, Microsoft
Satori, Facebook Entity Graph, Yahoo! Knowledge Graph and others. They are
intensively used in different application scenarios such as search,
question answering, natural language processing, data integration and
analytics, and for specialised areas such as digital
humanities, business, life science and more.

However, due to the diversity of data sources and limitations of present
knowledge
extraction methods, most knowledge graphs face a variety of quality issues
such as noise and vague data, inconsistency, inaccurate and out-of-date
data, incomplete information, and poor interlinking between KGs. To
facilitate wide adoption and advanced usage, it is crucial to ensure the
quality of knowledge graphs.

There are still big gaps between present state of quality engineering
techniques and high quality KGs and their effective applications.
Therefore, this workshop aims to address not only the challenges and
state-of-the-art solutions in quality assessment and improvement for
knowledge graphs, but also challenges for effectively employing reliable
KGs in different domains.

QEKGraph welcomes original research contributions crossing Data Quality and
knowledge graph management and consumption. Scholars who have conducted
research or developed impactful applications are invited to submit full
papers with appropriately evaluated contributions. QEKGraph also welcomes
vision/position papers on novel challenges or approaches to existing
problems (short papers). Topics on which potential submitters are invited
to contribute include, but are not limited to:

- Quality issues in knowledge graphs
- Quality assessment metrics and measures
- Representation of quality assessment results
- Data cleaning and knowledge graphs
- Outlier detection in knowledge graphs
- Triple classification and ranking
- Trust and provenance of knowledge graphs
- Data integration and quality control
- Evaluation of quality of links in the Web of Data
- Evaluation of link prediction methods
- Evaluation benchmark and datasets
- Multilingual knowledge graphs and quality control
- Quality assessment at scale
- Crowdsourcing and knowledge graph quality
- Quality of specialised knowledge graphs
- Trust and reliability of digital humanities and social science data
- Advancing education with data quality engineering

Submissions in all the categories mentioned above (full or short papers)
will be
peer-reviewed by acknowledged researchers familiar with both scientific
communities. Accepted papers will be published as online proceedings
courtesy of CEUR-WS.org.

# IMPORTANT DATES
Submission deadline: [EXTENDED] Friday, September 29, 2017*
Notification to authors: Friday, October 13, 2017*
Camera-ready due on: Sunday, October 22, 2017*
Workshop day: Monday, December 4, 2017 - to be confirmed
(*) All deadlines are 23:59 Hawaii time

# SUBMISSION INSTRUCTIONS
All papers must represent original and unpublished work that is not
currently under
review. Papers will be evaluated according to their significance,
originality, technical content, style, clarity, and relevance to the
workshop.

We welcome the following types of contributions:
- Full papers (up to 6 pages)
- Short papers (up to 4 pages)
All submissions must be PDF documents written in English and formatted
according to ACM SIG Proceedings guidelines [
https://www.acm.org/publications/proceedings-template]. Papers are to be
submitted through the Easychair Conference Management System  [
https://easychair.org/conferences/?conf=qekgraph2017]. Page limits are
inclusive of references and appendices, if any.

# PROGRAM COMMITTEE

- Riccardo Albertoni, Istituto per la Matematica Applicata e Tecnologie
Informatiche "Enrico Magenes", Italy
- Panos Alexopoulos, Textkernel B.V., Netherlands
- Mathieu d’Aquin, Insight Centre Galway, Ireland
- Helena Bermúdez-Sabel, Universidad de Educación a Distancia (UNED), Spain
- Oscar Corcho, Universidad Politécnica de Madrid, Spain
- Mariana Curado Malta, Polythecnic of Oporto, Portugal
- Marilena Daquino, Digital Humanities, University of Bologna, Italy
- Jeremy Debattista, Adapt Centre, Trinity College Dublin, Ireland
- Wassim Derguech, Insight Centre Galway, Ireland
- Anastasia Dimou, Ghent University - IMEC, Belgium
- Lisa Ehrlinger, Johannes Kepler University, Austria
- Raúl García-Castro, Universidad Politécnica de Madrid, Spain
- Xianpei Han, Chinese Academy of Sciences, China
- Oktie Hassanzadeh, IBM Thomas J. Watson Research Center, United States
- Wei Hu, Nanjing University, China
- Sangha Nam, KAIST, Korea
- Francesco Osborne, The Open University, UK
- Mariano Rico, Universidad Politécnica de Madrid, Spain
- Mariano Rodriguez-Muro, IBM Thomas J. Watson Research Center, United
States
- Cristina Sarasua, Universität Koblenz-Landau, Germany
- Bahar Sateli, Concordia University, Canada
- Boris Villazon-Terrazas, Fujitsu Laboratories of Europe, Madrid, Spain
- Xin Wang, Tianjin University, China
- Amrapali Zaveri, Maastricht University, The Netherlands