The Clio project: managing heterogeneity

By Renée J. Miller, Mauricio A. Hernández, L. Haas, Lingling Yan, C. T. H. Ho, Ronald Fagin, Lucian Popa. SGMD, 2001

400 citations recorded by the source corpus.

Clio is a system for managing and facilitating the complex tasks of heterogeneous data transformation and integration. In Clio, we have collected together a powerful set of data management techniques that have proven invaluable in tackling these difficult problems. In this paper, we present the underlying themes of our approach and present a brief case study.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/ddf0082c99e79077e4a89743446bf3fb911a4d6b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Ihab F. Ilyas
2. Joseph M Hellerstein
3. Nan Tang
4. Kunal Verma
5. Hong Hai Do
6. Erhard Rahm
7. Sanjay Krishnan
8. Mourad Ouzzani

In Computer Networks and Communications

1. Joseph M Hellerstein
2. Samuel Madden
3. Ihab F. Ilyas
4. Kunal Verma
5. Hong Hai Do
6. M. Stonebraker
7. Erhard Rahm
8. Amit P. Sheth

In Information Systems and Management

1. Samuel Madden
2. M. Stonebraker
3. Joseph M Hellerstein
4. Benjamin C. Pierce
5. Ihab F. Ilyas
6. Daniel S. Weld

Citations in the corpus

• Web Service Semantics - WSDL-S (2005, methodology): “Semi-automating the process of elaborating has been discussed in [ MHHYHFP01 , DR02].”
• Ground: A Data Context Service (2017, background): “The Clio project is a good example of research work on this class of schema-centric data integration [25].”
• Combinators for bi-directional tree transformations: a linguistic approach to the view update problem (2005, background): “[31] describe Clio, a system for managing heterogenous transformation and integration.”
• Ontological Smoothing for Relation Extraction with Minimal Supervision (2012, methodology): “’s tool Clio (Miller, Haas, and Hernández 2000)(Miller et al. 2001) generates complex SQL queries as mappings, and ranks these by heuristics.”
• Comparison of Schema Matching Evaluations (2002, neutral): “, Autoplex [ 1], Automatch [ 2], Clio [ 22, 16], COMA [ 7], Cupid [ 14], Delta [ 6 ], DIKE [ 19], EJX [ 10]1 , GLUE [ 9], LSD [ 8], MOMIS (and ARTEMIS) [ 3, 5 ], SemInt [ 11, 12, 13], SKAT [ 18], Similarity Flooding (SF) [ 15], and TranScm [ 17].”
• COMA - A System for Flexible Combination of Schema Matching Approaches (2002, methodology): “Numerous researchers have addressed the schema matching problem either for specific applications [ 1, 4, 5, 7, 8, 9, 11, 15, 16] or in a more generic way for different applications and schema languages [ 12, 13, 14].”
• Bidirectional Transformations: A Cross-Discipline Perspective (2009, background): “– Data Transformation, Integration, and Exchange: to map data across paradigms, merge it from multiple sources, and exchange it between sources [44, 47, 49, 57, 68, 82, 86].”
• Seeping Semantics: Linking Datasets Using Word Embeddings for Data Discovery (2018, methodology): “Tools such as COMA [32], Harmony [33], S-Match [34] and CLIO [35] have been developed for schema matching.”
• Structured databases on the web: observations and implications (2004, neutral): “, Information Manifold [19], TSIMMIS [20], Clio [21]).”