[ESWC 2015] Call for Challenge: Schema-agnostic Queries over Large-schema Databases

** apologies for cross-posting **

==== Call for Challenge: 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: February 15, 2015
- Final version of challenge training set: February 16, 2015
- Challenge paper submission deadline: March 3, 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) topics:

- 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, focsuing 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
Elena Cabrio, INRIA Sophia-Antipolis, France
Souleiman Hasan, DERI/Insight, Ireland
Saeedeh Shekarpour, Bonn University, Germany

Received on Friday, 13 February 2015 15:15:53 UTC