An Approach to Resolving Semantic Heterogeneity in a Federation of Autonomous, Heterogeneous Database Systems

Hammer, Joachim; McLeod, Dennis

doi:10.1142/s0218215793000046

Cited by 88 publications

(33 citation statements)

References 3 publications

(3 reference statements)

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“…Semantic information is effectively encoded in the MSL rules that do the integration. There are many projects that follow MedMaker's "structural" approach [Ber91, DH86, B+86], as well as many projects that follow a semantic approach [HM93,H+92]. We believe that the power of the structural approach, along with the flexibility, generality, and conciseness of OEM and MSL make the "structural" approach a better candidate for the integration of widely heterogeneous and semistructured information sources.…”

Section: Related Work and Discussionmentioning

confidence: 99%

The Stanford IBM Management of Multiple Information Systems (TSIMMIS) -- Stanford

Garcia-Moina¹

2000

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 222024302, and to the Office of Management and Budget, Paperwork Reduction Project 10704-0188), Washington, DC 20503. AGENCY USE ONLY (Leave blank)2. REPORT DATE MARCH 2000 REPORT TYPE AND DATES COVEREDFINAL REPORT FOR 09/30/1993 -09/30/1999 4. TITLE AND SUBTITLE THE STANFORD IBM MANAGEMENT OF MULTIPLE INFORMATION SYSTEMS (TSIMMIS) -STANFORD AUTHOR(S)HECTOR GARCIA-MOINA, PH.D. FUNDING NUMBERSC F33615-93-1-1339 PE 62301 PR A004 TA 01 WU 01 PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)STANFORD 12b. DISTRIBUTION CODE ABSTRACT (Maximum 200 words)OBJECTIVE: to improve the access and utility of heterogeneously distributed information. BACKGROUND: DARPA awarded this effort as sister effort to TSIMMIS-IBM. This work develops techniques to access, integrate, and utilize distributed heterogeneous information. SUBJECT TERMS Heterogeneous distributed information, Intelligent Query Processing, Databases The TSIMMIS Project Final ReportThe goal of the Tsimmis Project was to develop tools that facilitate the rapid integration of heterogeneous information sources that may include both structured and unstructured data. The project developed components that extract properties from unstructured objects, that translate information into a common object model, that combine information from several sources, that allow browsing of information, and that manage constraints across heterogeneous sites. Tsimmis was a joint project between Stanford and the IBM Almaden Research Center.A common problem facing many organizations today is that of multiple, disparate information sources and repositories, including databases, object stores, knowledge bases, file systems, digital libraries, information retrieval systems, and electronic mail systems. Decision makers often need information from multiple sources, but are unable to get and fuse the required information in a timely fashion due to the difficulties of accessing the different systems, and due to the fact that the information obtained can be inconsistent and contradictory. The TSIMMIS tools support integrated access to multiple information sources, and ensure that the information obtained is consistent.The enclosed papers give a comprehensive summary of the project and describe the major results obtained. In short, the results include:• AbstractThe goal of the Tsimmis Project is to develop tools that facilitate the rapid integration of heterogeneous information sources that may include both structured and unstructure...

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Section: Related Work and Discussionmentioning

confidence: 99%

The Stanford IBM Management of Multiple Information Systems (TSIMMIS) -- Stanford

Garcia-Moina¹

2000

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“…Many of the proposed solutions try to derive a common ontology by some (semi) automatic process, see for instance [1,3,5,7,12]. These approaches heavily rely on assumptions such as:…”

Section: Problems In Current Approachesmentioning

confidence: 99%

Automatic ontology mapping for agent communication

Wiesman¹,

Roos²,

Vogt³

2002

Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems Part 2 - AAMAS '02

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Agent communication languages such as ACL and KQML provide a standard for agent communication. These languages enable an agent to specify the intention and the content of a message as well as the protocol, the language, and the ontology that are used. For the protocol and the language some standards are available and should be known by the communicating agents.The ontology used in a communication depends on the subject of the communication. Since the number of subjects is almost infinite and since the concepts used for a subject can be described by different ontologies, the development of generally accepted standards will take a long time. This lack of standardization, which hampers communication and collaboration between agents, is known as the interoperability problem. To overcome the interoperability problem, agents must be able to establish a mapping between their ontologies. This paper investigates a new approach to the interoperability problem. The proposed approach requires neither a correspondence between concepts used in the ontologies nor a correspondence between the structure of the ontologies. It only requires that some instances of the subject about which the agents try to communicate are known by both agents. Acknowledgement: -Contact information:

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“…As highlighted in Section 2.1, for two parties to interoperate it is not enough to guarantee that the data flows across, but that they both build a semantic representation of the data that is consistent across the components boundaries. The data problem has been defined in Hammer and McLeod [24] as:…”

Section: Introductionmentioning

confidence: 99%

Interoperability in Complex Distributed Systems

Blair

Paolucci

Grace

et al. 2011

Lecture Notes in Computer Science

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Abstract. Distributed systems are becoming more complex in terms of both the level of heterogeneity encountered coupled with a high level of dynamism of such systems. Taken together, this makes it very difficult to achieve the crucial property of interoperability that is enabling two arbitrary systems to work together relying only on their declared service specification. This chapter examines this issue of interoperability in considerable detail, looking initially at the problem space, and in particular the key barriers to interoperability, and then moving on to the solution space, focusing on research in the middleware and semantic interoperability communities. We argue that existing approaches are simply unable to meet the demands of the complex distributed systems of today and that the lack of integration between the work on middleware and semantic interoperability is a clear impediment to progress in this area. We outline a roadmap towards meeting the challenges of interoperability including the need for integration across these two communities, resulting in middleware solutions that are intrinsically based on semantic meaning. We also advocate a dynamic approach to interoperability based on the concept of emergent middleware.

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An Approach to Resolving Semantic Heterogeneity in a Federation of Autonomous, Heterogeneous Database Systems

Cited by 88 publications

References 3 publications

The Stanford IBM Management of Multiple Information Systems (TSIMMIS) -- Stanford

The Stanford IBM Management of Multiple Information Systems (TSIMMIS) -- Stanford

Automatic ontology mapping for agent communication

Interoperability in Complex Distributed Systems

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