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FINAL CALL FOR PAPERS
Journal of Web Semantics
Special Issue on Dealing with the Messiness of the Web of Data
submission: 1 February 2011
to appear: January 2012
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(Guest editors: Stefan Schlobach, Craig A. Knoblock)
Description
Research on the Semantic Web, which is now in its second decade, has had
a tremendous success in encouraging people to publish data on the Web in
structured, linked, and standardized ways. The success of what has now
become the Web of Data can be read from the sheer number of triples available
within the Linked-Open Data, Linked Life Data and Open-Government initiatives.
However, this growth in data makes many of the established assumptions
inappropriate and offers a number of new research challenges.
In stark contrast to early Semantic Web applications that dealt with small,
hand-crafted ontologies and data-sets, the new Web of Data comes with a plethora
of contradicting world-views and contains incomplete, inconsistent, incorrect,
fast-changing and opinionated information. This information not only comes
from academic sources and trustworthy institutions, but is often community
built, scraped or translated.
In short: the Web of Data is messy, and methods to deal with this messiness
are paramount for its future.
For this special issue we seek articles describing foundational and theoretical
work as well as technological solutions for dealing with the messiness of the
Web of Data. More specifically, we expect submissions on (but not restricted to)
the following topics in the context of the Web of Data:
* Knowledge Representation in the presence of messy
* Context and multi-dimensionality
* Ontology and data versioning
* Enforcing and encouraging conventions
* Representation of uncertain, incomplete and inconsistent data
* Emergent semantics and self-organizing behaviour
* Querying and reasoning over the messy Web of Data
* Schemaless querying and integration
* Dataspaces for the Web of Data
* Federated querying
* Reasoning over uncertain, incomplete and inconsistent data
* Quantitative and statistical methods
* Data integration
* Identify resolution and record linkage
* Ontology Alignment
* Bridging structured and unstructured data
* Knowledge extraction from noisy data
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Important Dates
We will aim at an efficient publication cycle in order to guarantee prompt
availability of the published results. We will review papers on a rolling
basis as they are submitted and explicitly encourage submissions well before
the submission deadline. Submit papers online at the journal's Elsevier Web
site.
Submission deadline: 1 February 2011
Author notification: 15 June 2011
Revisions submitted: 1 August 2011
Final decisions: 15 September 2011
Publication: 1 January 2012
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Instructions for submission:
* The submission website for this journal is located at:
http://ees.elsevier.com/jws
* To ensure that all manuscripts are correctly identified for inclusion
into the special issue you are editing, it is important that authors select
"S.I.: Messiness of the Web of Data"
when they reach the "Article Type" step in the submission process.
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Guest Editors/Contacts
Stefan Schlobach (contact) -- Vrije Universiteit Amsterdam -- [email protected]
Craig A. Knoblock -- University of Southern California -- [email protected]
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Some example problems that would be interesting for this special issue:
1) Similarity Search: Often users are interested in finding similar resources
on the
WoD. For example, find cities like Amsterdam or compare universities across
Europe.
Here, users may not be able to specifically identify the desired overlap.
Instead,
it is up to the query answering system to identify the overlap and supply
reasonable
answers.
2) Schemaless Query: One of the positive things about the WoD is the ability
for data
providers and consumers to use their preferred schema. However, this makes it
difficult
to query new data sources. Users must discover, which schema is used.
Furthermore, it
makes queries across data sources even more difficult because mappings between
vocabularies must be available. We believe that approximation can help
alleviate this
problem by finding nswers "close enough" to the posed query's schema.
3) Robust Query: Misspellings, misuse of vocabulary, violations of schema
constraints,
all these are part of daily life on the WoD. Today, technologies either skip
over such
data or must contain workarounds to deal with it. A systematic approach to
dealing with
these issues using approximation techniques, would provide a more usable WoD.
4) Aggregated Search Results: answers to more sophisticated queries do not
reside all
within one triple store. Only by aggregating facts from multiple stores can
answers be
provided. While federation can virtually provide a single triple store, it has
limitations in terms of the consistency required across the underlying triple
stores.
We believe that approximation can provide a mechanism to enable more robust
aggregated
search results and federation.
5) Robust extraction: most data that is useful for the Web of Data is not build
using
Semantic technology but stems from traditional databases. Often this data is
translated,
or even scraped from Web Services or even html pages. Linking this information
in well-
understood and Semantically correct are crucial for the WoD.
--
Stefan Schlobach, PhD Artificial Intelligence Group
Faculty of Science Vrije Universiteit Amsterdam
[email protected] http://www.few.vu.nl/~schlobac
