- From: Mauro Dragoni <dragoni@fbk.eu>
- Date: Fri, 13 Feb 2015 16:15:05 +0100
- To: Semantic Web <semantic-web@w3.org>, public-lod@w3.org, public-ontolex@w3.org, CHI-ANNOUNCEMENTS@listserv.acm.org, confs-submit@hri.org, aisworld@lists.aisnet.org, planetkr@kr.org, Community@sti2.org, semanticweb@yahoogroups.com, events_calendar@acm.org, linguist@linguistlist.org, dbpedia-discussion@lists.sourceforge.net, dbpedia-developers@lists.sourceforge.net, public-ldp@w3.org, semantic_web_doktorandennetzwerk@lists.spline.inf.fu-berlin.de, lod2@lists.okfn.org, public-vocabs@w3.org
** 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 GENERAL CHAIR - Fabien Gandon (Inria, Sophia Antipolis, France) CHALLENGE COORDINATORS - Elena Cabrio (Inria, Sophia Antipolis, France) - Milan Stankovic (SEPAGE, Paris, France) CHALLENGE CHAIRS - Andre Freitas, University of Passau, Germany, DERI/Insight, Ireland - Christina Unger, Bielefeld University, Germany IMPORTANT DATES - 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 THE CHALLENGE IN A NUTSHELL To create a query mechanism that semantically matches schema-agnostic user queries to knowledge base elements GOAL To support easy querying over complex databases with large schemata, relieving users from the need to understand the formal representation of the data RELEVANCE 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. SUBMISSIONS 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. ABOUT THE CHALLENGE 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 community. 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: SELECT ?y { 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/> SELECT ?x { ?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" EVALUATION 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. PRIZES A financial prize (to be announced) will be given to the authors of the best-performing system and/or most original contribution. HOW TO PARTICIPATE High quality original papers should be submitted via EasyChair: https://easychair.org/conferences/?conf=saq2015 Long papers should have at maximum 12 pages, and short papers 6 pages. All submissions must conform with the LNCS format (http://www.springer.de/comp/lncs/authors.html). PROGRAM COMMITTEE 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 15:15:52 UTC