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Deadline Extension: Schema-agnostic Queries over Large-schema Databases (SAQ-2015) [ESWC Challenge]

From: André Freitas <andrenfreitas@gmail.com>
Date: Sat, 7 Mar 2015 22:08:58 +0000
Message-ID: <CAGYJJaMb-QOW5cGyrWZadBaGYAkAxG77TuB1GgtuB4sVCwtREA@mail.gmail.com>
To: undisclosed-recipients:;
** apologies for cross-posting **

==== Call for Challenge Participation & Papers: Schema-agnostic Queries
over Large-schema Databases (SAQ-2015) "Abstracting users from the
representation of the data" ESWC 2015 - Semantic Web Challenge ====

Challenge Website: https://sites.google.com/site/eswcsaq2015/

12th Extended Semantic Web Conference (ESWC) 2015
Dates: May 31 - June 4, 2015
Venue: Portoroz, Slovenia
Hashtag: #eswc2015
Feed: @eswc_conf
Site: http://2015.eswc-conferences.org

- Fabien Gandon (Inria, Sophia Antipolis, France)

- Elena Cabrio (Inria, Sophia Antipolis, France)
- Milan Stankovic (SEPAGE, Paris, France)

- Andre Freitas, University of Passau, Germany, DERI/Insight, Ireland
- Christina Unger, Bielefeld University, Germany

- Initial version of the challenge training set: February 1, 2015
- Submission of the intent to participate: March 23, 2015
- Final version of challenge training set: February 16, 2015
- Challenge paper submission deadline (extended): March 25, 2015
- Notification of acceptance: April 9, 2015
- Test data set published: April 9, 2015
- Report of the task results: April 9, 2015
- Camera-ready papers deadline: April 24, 2015


To create a query mechanism that semantically matches schema-agnostic user
queries to knowledge base elements.


To support easy querying over complex databases with large schemata,
relieving users from the need to understand the formal representation of
the data.


The increase in the size and in the semantic heterogeneity of database
schemas are bringing new requirements for users querying and searching
structured data.

At this scale it can become unfeasible for data consumers to be familiar
with the representation of the data in order to query it. At the center of
this discussion is the semantic gap between users and databases, which
becomes more central as the scale and complexity of the data grows.
Addressing this gap is a fundamental part of the Semantic Web vision.

Schema-agnostic query mechanisms aim at allowing users to be abstracted
from the representation of the data, supporting the automatic matching
between queries and databases. This challenge aims at emphasizing the role
of schema-agnosticism as a key requirement for contemporary database
management, by providing a test collection for evaluating flexible query
and search systems over structured data in terms of their level of
schema-agnosticism (i.e. their ability to map a query issued with the user
terminology and structure, mapping it to the dataset vocabulary). The
challenge is instantiated in the context of Semantic Web datasets.


SAQ-2015 invites submissions of papers targeting the following (or related)

- Schema-agnostic query approaches and systems.
- Demonstrations of schema-agnostic query approaches.
- Usability and user-interface aspects for schema-agnostic queries.
- Formal models for schema-agnostic queries.
- Analysis of the semantic aspects involved in query-database matching.
- Evaluation methodologies for schema-agnostic queries.
- Entity search & schema-agnostic queries.
- Natural Language Interfaces & schema-agnostic queries.


The challenge aims at providing an evaluation test collection for
schema-agnostic query mechanisms, focusing on Semantic Web scenarios. The
large-schema and semantically heterogeneous nature of Semantic Web datasets
brings schema-agnosticism as a fundamental data management concern for this

The test collection supports the quantitative and qualitative evaluation of
degree of schema-agnosticism of different approaches.Since addressing
schema-agnostic queries is dependent on semantic approaches which need to
cope with different types of semantic matching between query and dataset,
the test collection explores different categories of semantic phenomena
involved in the challenge of matching schema-agnostic queries. Each query
is categorized according to the semantic mapping types. This categorization
supports a fine-grained qualitative and quantitative interpretation of the
evaluation results.

Participating systems (semantic query/search engines) will receive a set of
schema-agnostic queries over DBpedia 3.10 data. The task is to return the
correct answers for the query associated with the right interpretation of
the query under the evaluation dataset. Two categories of schema-agnostic
queries (tasks) are available:

Schema-agnostic SPARQL query

Consists of schema-agnostic queries following the syntax of the SPARQL
standard. The syntax and semantics of operators are maintained, while
different terminologies are used.

* Example I:

BillClinton hasDaughter ?x .
?x marriedTo ?y .

which maps to the following SPARQL query in the dataset vocabulary:

PREFIX : <http://dbpedia.org/resource/>
PREFIX dbpedia2: <http://dbpedia.org/property/>
PREFIX dbpedia: <http://dbpedia.org/ontology/>
PREFIX skos: <http://www.w3.org/2004/02/skos/core#>
PREFIX dbo: <http://dbpedia.org/ontology/>

SELECT   ?y  {
:Bill_Clinton dbpedia:child ?x .
?x dbpedia2:spouse ?y .

* Example II:

SELECT   ?x {
         ?x isA book .
         ?x by William_Goldman .
         ?x has_pages ?p .
         FILTER (?p > 300)

which maps to the following SPARQL query in the dataset vocabulary:

PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX : <http://dbpedia.org/resource/>
PREFIX dbpedia2: <http://dbpedia.org/property/>
PREFIX dbpedia: <http://dbpedia.org/ontology/>
         ?x rdf:type dbpedia:Book .
         ?x dbpedia2:author :William_Goldman .
         ?x dbpedia:numberOfPages ?p .
FILTER(?p > 300)

Schema-agnostic keyword query

Consists of schema-agnostic queries using keyword queries. In this case the
syntax and semantics of operators are different from the
SPARQL syntax.

* Example I:

"Bill Clinton daughter married to"

* Example II:

"Books by William Goldman with more than 300 pages"


The challenge provides a gold standard with the correct answers for each
query. Queries will be issued over DBpedia 3.10. A training dataset
consisting of 25 queries will be made available for the participants. 100
queries will be used to evaluate the systems. In order to participate in
the challenge, each system should submit the results in the format proposed
by the challenge. The organizers will then automatically calculate
precision, recall, mean reciprocal rank for each query and the associated
averages. Participants are required to submit their query execution time,
dataset enrichment time, and user-interaction disambiguation effort.


A financial prize (to be announced) will be given to the authors of the
best-performing system and/or most original contribution.


High quality original papers should be submitted via EasyChair:

Long papers should have at maximum 12 pages, and short papers 6 pages. All
submissions must conform with the LNCS format


Stefan Bischof, WU Economics/Siemens, Austria
Edward Curry, DERI/Insight, Ireland
Sebastian Walter, Bielefeld University, Germany
Siegfried Handschuh, University of Passau, Germany
Pierpaolo Basile, University of Bari, Italy
Axel Ngonga, University of Leipzig, Germany
Andre Freitas, University of Passau, Germany
Christina Unger, Bielefeld University, Germany
Stephane Campinas, DERI/Insight, Ireland
Honghan Wu, University of Aberdeen, UK
Vanessa Lopez, IBM Research, Ireland
Ahmed El-Roby, University of Waterloo, Canada
Tran Thanh, Graphinder/San Jose State University, USA
Pablo Mendes, IBM Research, USA
Francesco Guerra, University of Modena, Italy
Krisztian Balog, University of Stavanger, Norway
Souleiman Hasan, DERI/Insight, Ireland
Saeedeh Shekarpour, Bonn University, Germany
Received on Saturday, 7 March 2015 22:09:27 UTC

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