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Enterprise information integration (EII) is the ability to support a unified view of data and information for an entire organization. In a data virtualization application of EII, a process of information integration, using data abstraction to provide a unified interface for viewing all the data within an organization, and a single set of structures and naming conventions to represent this data; the goal of EII is to get a large set of heterogeneous data sources to appear to a user or system as a single, homogeneous data source.
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Data integration involves combining data residing in different sources and providing users with a unified view of them. This process becomes significant in a variety of situations, which include both commercial and scientific domains. Data integration appears with increasing frequency as the volume, complexity and the need to share existing data explodes. It has become the focus of extensive theoretical work, and numerous open problems remain unsolved. Data integration encourages collaboration between internal as well as external users. The data being integrated must be received from a heterogeneous database system and transformed to a single coherent data store that provides synchronous data across a network of files for clients. A common use of data integration is in data mining when analyzing and extracting information from existing databases that can be useful for Business information.
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Amit Sheth is a computer scientist at University of South Carolina in Columbia, South Carolina. He is the founding Director of the Artificial Intelligence Institute, and a Professor of Computer Science and Engineering. From 2007 to June 2019, he was the Lexis Nexis Ohio Eminent Scholar, director of the Ohio Center of Excellence in Knowledge-enabled Computing, and a Professor of Computer Science at Wright State University. Sheth's work has been cited by over 48,800 publications. He has an h-index of 117, which puts him among the top 100 computer scientists with the highest h-index. Prior to founding the Kno.e.sis Center, he served as the director of the Large Scale Distributed Information Systems Lab at the University of Georgia in Athens, Georgia.
Semantic matching is a technique used in computer science to identify information which is semantically related.
The BioCatalogue is a curated catalogue of Life Science Web Services. The BioCatalogue was launched in June 2009 at the Intelligent Systems for Molecular Biology Conference. The project is a collaboration between the myGrid project at the University of Manchester led by Carole Goble and the European Bioinformatics Institute led by Rodrigo Lopez. It is funded by the Biotechnology and Biological Sciences Research Council.
Apache Hive is a data warehouse software project. It is built on top of Apache Hadoop for providing data query and analysis. Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data.
Norman William Paton is a Professor in the Department of Computer Science at the University of Manchester in the UK where he co-leads the Information Management Group (IMG) with Carole Goble.
Semantic heterogeneity is when database schema or datasets for the same domain are developed by independent parties, resulting in differences in meaning and interpretation of data values. Beyond structured data, the problem of semantic heterogeneity is compounded due to the flexibility of semi-structured data and various tagging methods applied to documents or unstructured data. Semantic heterogeneity is one of the more important sources of differences in heterogeneous datasets.
Semantic queries allow for queries and analytics of associative and contextual nature. Semantic queries enable the retrieval of both explicitly and implicitly derived information based on syntactic, semantic and structural information contained in data. They are designed to deliver precise results or to answer more fuzzy and wide open questions through pattern matching and digital reasoning.
Laura M. Haas is an American computer scientist noted for her research in database systems and information integration. She is best known for creating systems and tools for the integration of heterogeneous data from diverse sources, including federated technology that virtualizes access to data, and mapping technology that enables non-programmers to specify how data should be integrated.
References
- ↑ Belhajjame, K.; Paton, N. W.; Embury, S. M.; Fernandes, A. A. A.; Hedeler, C. (2013). "Incrementally improving dataspaces based on user feedback". Information Systems. 38 (5): 656. CiteSeerX 10.1.1.303.1957 . doi:10.1016/j.is.2013.01.006.
- ↑ Belhajjame, K.; Paton, N. W.; Embury, S. M.; Fernandes, A. A. A.; Hedeler, C. (2010). "Feedback-based annotation, selection and refinement of schema mappings for dataspaces". Proceedings of the 13th International Conference on Extending Database Technology - EDBT '10. p. 573. CiteSeerX 10.1.1.298.3519 . doi:10.1145/1739041.1739110. ISBN 9781605589459.
- ↑ Dong, X.; Halevy, A. (2007). "Indexing dataspaces". Proceedings of the 2007 ACM SIGMOD international conference on Management of data - SIGMOD '07. p. 43. doi:10.1145/1247480.1247487. ISBN 9781595936868. S2CID 1184444.
- ↑ Howe, B.; Maier, D.; Rayner, N.; Rucker, J. (2008). "Quarrying dataspaces: Schemaless profiling of unfamiliar information sources". 2008 IEEE 24th International Conference on Data Engineering Workshop. p. 270. doi:10.1109/ICDEW.2008.4498331. ISBN 978-1-4244-2161-9. S2CID 14039616.
- ↑ Sarma, A. D.; Dong, X. (L.; Halevy, A. Y. (2009). "Data Modeling in Dataspace Support Platforms". Conceptual Modeling: Foundations and Applications. Lecture Notes in Computer Science. Vol. 5600. pp. 122–138. doi:10.1007/978-3-642-02463-4_8. ISBN 978-3-642-02462-7.
- ↑ Franklin, M.; Halevy, A.; Maier, D. (2005). "From databases to dataspaces". ACM SIGMOD Record. 34 (4): 27. doi:10.1145/1107499.1107502. S2CID 14092111.
- ↑ Otto, Boris; Auer, Sören; Cirullies, Jan (February 2016). "Industrial Data Space: Digital Souvereignity Over Data" (PDF). ResearchGate.
- ↑ Otto, Boris; ten Hompel, Michael; Wrobel, Stefan (2022). "Designing Data Spaces - The Ecosystem Approach to Competitive Advantage" (PDF). Springer. ISBN 978-3-030-93974-8.