scispace - formally typeset
Search or ask a question
Topic

Ontology-based data integration

About: Ontology-based data integration is a research topic. Over the lifetime, 11065 publications have been published within this topic receiving 216888 citations.


Papers
More filters
Proceedings ArticleDOI
03 Jul 2006
TL;DR: An ontology-based framework for context-aware mobile learning is proposed that is designed to extract from a source ontology a lightweight target ontology by firing a set of rules based on the learner profile.
Abstract: Mobile learning is becoming an important research topic as people are increasingly connected through smart phones that combine telephony, computing, messaging, and multimedia. The process of designing, communicating and presenting learning resources for mobile learners poses new challenges to the research community. This is mainly due to the limited bandwidth of wireless networks, limited resource available on mobile devices, and the special requirements of mobile learners. In this paper, an attempt is made to solve some of these problems by proposing an ontology-based framework for context-aware mobile learning. The system consists mainly of a rule-based ontology and a search agent. The rule-based ontology component is driven by the learner profile to contextualize learning content accordingly. The goal is to extract from a source ontology a lightweight target ontology by firing a set of rules based on the learner profile. The extracted conceptual knowledge is then mapped to a set of learning objects that meet the technical requirements of the used mobile technology. The mapping is geared by a search agent that searches a set of distributed learning objects repositories for feasible lightweight learning objects.

98 citations

Journal ArticleDOI
01 Jan 2012-Database
TL;DR: The Units Ontology (UO) is presented, an ontology currently being used in many scientific resources for the standardized description of units of measurements for interoperability and semantic information processing between diverse biomedical resources and domains.
Abstract: Units are basic scientific tools that render meaning to numerical data. Their standardization and formalization caters for the report, exchange, process, reproducibility and integration of quantitative measurements. Ontologies are means that facilitate the integration of data and knowledge allowing interoperability and semantic information processing between diverse biomedical resources and domains. Here, we present the Units Ontology (UO), an ontology currently being used in many scientific resources for the standardized description of units of measurements.

98 citations

01 Jan 2007
TL;DR: This work has developed a set of tools and services to support the process of achieving consensus on such a common shared ontologies by geographically distributed groups and describes applications using these tools to achieve consensus on ontologies and to integrate information.
Abstract: Information integration is enabled by having a precisely defined common terminology. We call this combination of terminology and definitions an ontology . We have developed a set of tools and services to support the process of achieving consensus on such a common shared ontologies by geographically distributed groups. These tools make use of the world-wide web to enable wide access and provide users with the ability to publish, browse, create, and edit ontologies stored on an ontology server. Users can quickly assemble a new ontology from a library of modules. We discuss how our system was constructed, how it exploits existing protocols and browsing tools, and our experience supporting hundreds of users. We describe applications using our tools to achieve consensus on ontologies and to integrate information. The ontology server may be accessed through the URL http://www-ksl-svc.stanford.edu:5915/

98 citations

Journal ArticleDOI
TL;DR: A method for corpus-driven ontology design: extracting conceptual hierarchies from arbitrary domain-specific collections of texts, employing statistical techniques initially to elicit a conceptual hierarchy, which is then augmented through linguistic analysis.
Abstract: This paper discusses a method for corpus-driven ontology design: extracting conceptual hierarchies from arbitrary domain-specific collections of texts. These hierarchies can form the basis for a concept-oriented (onomasiological) terminology collection, and hence may be used as the basis for developing knowledge-based systems using ontology editors. This reference to ontology is explored in the context of collections of terms. The method presented is a hybrid of statistical and linguistic techniques, employing statistical techniques initially to elicit a conceptual hierarchy, which is then augmented through linguistic analysis. The result of such an extraction may be useful in information retrieval, knowledge management, or in the discipline of terminology science itself.

98 citations


Network Information
Related Topics (5)
Server
79.5K papers, 1.4M citations
84% related
Graph (abstract data type)
69.9K papers, 1.2M citations
84% related
Software development
73.8K papers, 1.4M citations
84% related
User interface
85.4K papers, 1.7M citations
84% related
Support vector machine
73.6K papers, 1.7M citations
83% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202337
2022149
202111
202011
201919
201843