For single databases, primary hindrances for end-user access are the volume of data that is becoming available, the lack of abstraction, and the need to understand the representation of the data. When information is combined from multiple databases, the major concern is the mismatch encountered in information representation and structure. Intelligent and active use of information requires a class of software modules that mediate between the workstation applications and the databases. It is shown that mediation simplifies, abstracts, reduces, merges, and explains data. A mediator is a software module that exploits encoded knowledge about certain sets or subsets of data to create information for a higher layer of applications. A model of information processing and information system components is described. The mediator architecture, including mediator interfaces, sharing of mediator modules, distribution of mediators, and triggers for knowledge maintenance, are discussed.
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Masmoudi MBen Abdallah Ben Lamine SKarray MArchimede BBaazaoui Zghal H(2024)Semantic Data Integration and Querying: A Survey and ChallengesACM Computing Surveys10.1145/365331756:8(1-35)Online publication date: 26-Apr-2024
Boltz NGetir Yaman SInverardi PDe Lemos RVan Landuyt DZisman ABaresi LMa XPasquale L(2024)Human empowerment in self-adaptive socio-technical systemsProceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems10.1145/3643915.3644082(200-206)Online publication date: 15-Apr-2024
Wrembel R(2023)Data Integration Revitalized: From Data Warehouse Through Data Lake to Data MeshDatabase and Expert Systems Applications10.1007/978-3-031-39847-6_1(3-18)Online publication date: 28-Aug-2023
COOPIS '97: Proceedings of the Second IFCIS International Conference on Cooperative Information Systems
The AURORA mediator system employs a novel 2-tier, plug-and-play mediation model that is designed to facilitate access to a large number of heterogeneous data sources. The paper describes AURORA's mediation model and a suite of techniques used by a ...
The author argues for a concept that is intended to help computer users survive the continuing data (not, one notices, knowledge or information) explosion. Because of the data surfeit, we have trouble getting enough knowledge. Selection (reducing the volume) and abstraction are our tools in dealing with this problem. Where abstractions are available for accessing some data, however, they are likely not to match the abstractions available for other data.
If we had intelligent assistants, or <__?__Pub Fmt italic>mediators<__?__Pub Fmt /italic> (Wiederhold avoids the AI term <__?__Pub Fmt italic>agent<__?__Pub Fmt /italic>, although he draws attention to the similarity between agents and mediators), we could issue requests such as, “Based on the models used by the best economists, summarize the evolution of world trade over the past five years.” (Isn't that better than SQL__?__) This example task involves making the abstract request concrete through judgment, model selection, database connection, data look-up, model execution, data interpretation and reduction, presentation of results, and probably cooperation among several such assistants, which in turn involves dealing with the abstractions they respond to. Thus is knowledge created from data. The author sees automating such assistants as the solution to the data explosion.
In a layered architecture, mediators are intermediate between one or more DBMSs and the applications that need the information. They convert requests into data-specific queries, which they pass downward, and convert data into information and pass it upward. The interface protocol is a form of universal object access language, analogous to the interface SQL provides to databases, but based on useful abstractions, not data dictionary entries. The paper goes on to discuss some implementation issues, such as What language is used for mediator requests__?__ What sort of intelligence do mediators need__?__ How do mediators, which are relatively autonomous, cooperate__?__ Can mediator knowledge be kept up to date through triggering events__?__ and Can mediators learn__?__ The author goes on to imagine (in a sidebar) a world in which<__?__Pub Caret> mediators might be available for rent—knowledge as commodity.
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Masmoudi MBen Abdallah Ben Lamine SKarray MArchimede BBaazaoui Zghal H(2024)Semantic Data Integration and Querying: A Survey and ChallengesACM Computing Surveys10.1145/365331756:8(1-35)Online publication date: 26-Apr-2024
Boltz NGetir Yaman SInverardi PDe Lemos RVan Landuyt DZisman ABaresi LMa XPasquale L(2024)Human empowerment in self-adaptive socio-technical systemsProceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems10.1145/3643915.3644082(200-206)Online publication date: 15-Apr-2024
Wrembel R(2023)Data Integration Revitalized: From Data Warehouse Through Data Lake to Data MeshDatabase and Expert Systems Applications10.1007/978-3-031-39847-6_1(3-18)Online publication date: 28-Aug-2023
Leclercq ÉGillet AGrison TSavonnet M(2022)Polystore and Tensor Data Model for Logical Data Independence and Impedance Mismatch in Big Data AnalyticsTransactions on Large-Scale Data- and Knowledge-Centered Systems XLII10.1007/978-3-662-60531-8_3(51-90)Online publication date: 11-Mar-2022
Wrembel R(2022)Data Integration, Cleaning, and Deduplication: Research Versus Industrial ProjectsInformation Integration and Web Intelligence10.1007/978-3-031-21047-1_1(3-17)Online publication date: 28-Nov-2022
Corcho OPriyatna FChaves-Fraga D(2020)Towards a new generation of ontology based data accessSemantic Web10.3233/SW-19038411:1(153-160)Online publication date: 1-Jan-2020
Manolescu I(2020)Integrating (Very) Heterogeneous Data Sources: A Structured and an Unstructured PerspectiveAdvances in Databases and Information Systems10.1007/978-3-030-54832-2_3(15-20)Online publication date: 25-Aug-2020
Dernaika FCuppens-Boulahia NCuppens FRaynaud O(2019)Semantic Mediation for A Posteriori Log AnalysisProceedings of the 14th International Conference on Availability, Reliability and Security10.1145/3339252.3340104(1-10)Online publication date: 26-Aug-2019