The Use of Carin Language and Algorithms for Information Integration: The Picsel System

Goasdoué, François; Lattès, Véronique; Rousset, Marie-Christine

doi:10.1142/s0218843000000181

Cited by 96 publications

(70 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Each employee works for at least one project (4, 5), whereas each person and each project has a unique name (6,7,9,10). Both person names and project names are strings (8,11), whereas the attribute until associates objects with dates (14,15). In particular, any temporary employee has an associated date (which indicates the expiration date of her/his contract) (12), and everyone having a value for attribute until participates in the role WORKS-FOR (13).…”

Section: Dl-lite a Ontologiesmentioning

confidence: 99%

“…This issue is studied in [11,5], where specific mapping languages are proposed for linking data to ontologies. Such approaches, however, do not deal with the problem of the impedance mismatch between objects and values, which needs to be addressed by defining suitable mechanisms for mapping the data values to the objects in the ontology, and specifying how object identifiers can be built starting from data values.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Linking Data to Ontologies

Poggi

Lembo

Calvanese

et al. 2008

Journal on Data Semantics X

487

523

View full text Add to dashboard Cite

Abstract. Many organizations nowadays face the problem of accessing existing data sources by means of flexible mechanisms that are both powerful and efficient. Ontologies are widely considered as a suitable formal tool for sophisticated data access. The ontology expresses the domain of interest of the information system at a high level of abstraction, and the relationship between data at the sources and instances of concepts and roles in the ontology is expressed by means of mappings. In this paper we present a solution to the problem of designing effective systems for ontology-based data access. Our solution is based on three main ingredients. First, we present a new ontology language, based on Description Logics, that is particularly suited to reason with large amounts of instances. The second ingredient is a novel mapping language that is able to deal with the so-called impedance mismatch problem, i.e., the problem arising from the difference between the basic elements managed by the sources, namely data, and the elements managed by the ontology, namely objects. The third ingredient is the query answering method, that combines reasoning at the level of the ontology with specific mechanisms for both taking into account the mappings and efficiently accessing the data at the sources.

show abstract

Section: Dl-lite a Ontologiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Linking Data to Ontologies

Poggi

Lembo

Calvanese

et al. 2008

Journal on Data Semantics X

487

523

View full text Add to dashboard Cite

show abstract

“…In the mediator-based approach (Rousset, 2002), the different data remain located at their original sources. User queries are executed through a mediator-wrapper system (Goasdoué et al, 2000). A mediator reformulates queries according to the content of the various accessible data sources, while the wrapper extracts the selected data from the target source.…”

Section: Context and Issuesmentioning

confidence: 99%

Warehousing complex data from the web

Boussaïd

Darmont

Bentayeb

et al. 2008

IJWET

View full text Add to dashboard Cite

Data warehousing and Online Analytical Processing (OLAP) technologies are now moving onto handling complex data that mostly originate from the web. However, integrating such data into a decision-support process requires their representation in a form processable by OLAP and/or data mining techniques.We present in this paper a complex data warehousing methodology that exploits eXtensible Markup Language (XML) as a pivot language. Our approach includes the integration of complex data in an ODS, in the form of XML documents; their dimensional modelling and storage in an XML data warehouse; and their analysis with combined OLAP and data mining techniques. We also address the crucial issue of performance in XML warehouses.

show abstract

“…For example, if the current query contains the concept biopolymer which has the expansion protein t dna, the user would have the option of treating biopolymer as an atomic concept, whose sources are the union of all protein and dna sources, or of expanding and treating the disjuncts separately. If a more sophisticated rewriting system is used, as in DWQ [2] or PICSEL [4], it might be necessary for the user to work with the rewritten form of the query, as there may be little or no relation between the syntactic forms of the userÕs query and the plan.…”

Section: Interactive Improvement Of Soundness and Completenessmentioning

confidence: 99%

“…In recent years, a number of distributed query-processing systems have been developed in which the global schema and user queries are expressed in some form of description logic (DL) (for example, TAMBIS [1], DWQ [2], Information Manifold [3], PICSEL [4], SIMS [5]). The use of a DL as both high-level data description language and query language has several advantages:…”

Section: Introductionmentioning

confidence: 99%

Estimating the quality of answers when querying over description logic ontologies

Peim

Franconi

Paton

2003

Data & Knowledge Engineering

View full text Add to dashboard Cite

Information integration systems allow users to express queries over high-level conceptual models. However, such queries must subsequently be evaluated over collections of sources, some of which are likely to be expensive to use or subject to periods of unavailability. As such, it would be useful if information integration systems were able to provide users with estimates of the consequences of omitting certain sources from query execution plans. Such omissions can affect both the soundness (the fraction of returned answers which are returned) and the completeness (the fraction of correct answers which are returned) of the answer set returned by a plan. Many recent information integration systems have used conceptual models expressed in description logics (DLs). This paper presents an approach to estimating the soundness and completeness of queries expressed in the ALCQI DL. Our estimation techniques are based on estimating the cardinalities of query answers. We have have conducted some statistical evaluation of our techniques, the results of which are presented here. We also offer some suggestions as to how estimates for cardinalities of subqueries can be used to aid users in improving the soundness and completeness of query plans.

show abstract

The Use of Carin Language and Algorithms for Information Integration: The Picsel System

Cited by 96 publications

References 8 publications

Linking Data to Ontologies

Linking Data to Ontologies

Warehousing complex data from the web

Estimating the quality of answers when querying over description logic ontologies

Contact Info

Product

Resources

About