Rondo: a programming platform for generic model management

By Sergey Melnik, Erhard Rahm, Philip A. Bernstein. ACM SIGMOD Conference, 2003

392 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/fb60c9b08d6cd82550b274749573f1c829d2f2cd

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. Pavel Shvaiko
2. Jérôme Euzenat
3. Fausto Giunchiglia
4. Jayant Madhavan
5. Alon Y. Halevy
6. Philip A. Bernstein
7. Sergey Melnik
8. Anand Rajaraman

In Computer Networks and Communications

1. Pavel Shvaiko
2. Jérôme Euzenat
3. Fausto Giunchiglia
4. Jayant Madhavan
5. Philip A. Bernstein
6. Alon Y. Halevy
7. Sergey Melnik
8. Rachel Pottinger

In Information Systems

1. Pavel Shvaiko
2. Jérôme Euzenat
3. Fausto Giunchiglia
4. Philip A. Bernstein
5. Jayant Madhavan
6. Mikalai Yatskevich
7. Alon Y. Halevy
8. Sergey Melnik

Citations in the corpus

• Composing Mappings Among Data Sources (2003, background): “A second motivation for mapping composition comes from the area of model management [3, 23].”
• A Survey of Schema-Based Matching Approaches (2005, positive): “Some other innovations with respect to COMA, are in the set of elementary matchers based on rules, exploiting explicitly codified knowledge in ontologies, such as information about super-and sub-concepts, super-and sub-properties, etc.”
• Data integration: the teenage years (2006, background): “The goal of Model Management [13, 14, 80] is to provide an algebra for manipulating schemas and map­pings, so the same operations do not need to be reinvented for every new context and/or data model.”
• Merging Models Based on Given Correspondences (2003, background): “Rondo [12] is a model management system prototype that includes an alternate Merge definition based entirely on equality mappings.”
• S-Match: an Algorithm and an Implementation of Semantic Matching (2004, methodology): “We have compared S-Match with three state of the art schema-based matching systems, namely Cupid [12], COMA [4], and Similarity Flooding (SF) [15] as implemented within the Rondo system [14].”
• Semantic Matching: Algorithms and Implementation (2007, methodology): “The Similarity Flooding (SF) [35] approach, as implemented in Rondo [36], utilizes a hybrid matching algorithm based on the ideas of similarity propagation.”
• Model management 2.0: manipulating richer mappings (2007, methodology): “Indeed, the first implementation of a model management system followed this approach [69].”