Principles of dataspace systems

By Alon Y. Halevy, M. Franklin, David Maier. ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 2006

386 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/60fd48ec92a40a63a0f814d550ffc88663c9ff58

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Citations in the corpus

An Introduction to Duplicate Detection (2010, methodology): “The first use case is the prime example for data spaces [Halevy et al., 2006], namely personal information management [Dittrich et al.”
Data integration: the teenage years (2006, background): “[52] Alon Halevy, Michael Franklin, and David Maier.”
Management of probabilistic data: foundations and challenges (2007, background): “The system computes the answers, and for each answer computes an output probability score representing its con.dence in that answer.”
State of the nation in data integration for bioinformatics (2008, background): “Recent proposals on Dataspaces [32] argue that the way forward is best effort evidence-based integration and auto-generated mappings—echoing our view that just enough and just in time integration is desirable and practical.”
Linked Data - The Story So Far (2009, neutral): “Dataspaces provide a target system architecture around which ongoing research on reference reconciliation, schema matching and mapping, data lineage, data quality and information extraction are unified ( Halevy et al., 2006 ).”
The RDF-3X engine for scalable management of RDF data (2010, background): “In this sense, the notion of RDF triples fits well with the modern notion of data spaces and its “pay as you go” philosophy [21].”
Data integration with uncertainty (2007, background): “Extending data integration systems to handle uncertainty is also a key step to realizing Dataspace Support Platforms [15].”
Big data integration (2013, neutral): “[22], [7], [8], [42], [26], [17], [25], [43].”
Provenance in Databases: Why, How, and Where (2009, background): “, data exchange [47], data integration [48], and dataspaces [45]).”
RDF-3X: a RISC-style engine for RDF (2008, background): “In this sense, the notion of RDF triples fits well with the modern notion of data spaces and its “pay as you go” philosophy [18].”
Managing uncertainty and vagueness in description logics for the Semantic Web (2008, background): “This can be handled via probabilistic data integration by associating with every web source a probability describing its degree of reliability [148,45].”
Web-Scale Data Integration: You can afford to Pay as You Go (2007, background): “Hence, it is crucial that we leverage as much as possible feedback we can get from users or administrators of the system [19].”