Gram: a graph data model and query languages
ECHT '92 Proceedings of the ACM conference on Hypertext
GOOD: a graph-oriented object database system
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
A query language for a Web-site management system
ACM SIGMOD Record
Designing OQL: allowing objects to be queried
Information Systems
SchemaSQL: An extension to SQL for multidatabase interoperability
ACM Transactions on Database Systems (TODS)
UnQL: a query language and algebra for semistructured data based on structural recursion
The VLDB Journal — The International Journal on Very Large Data Bases
Provenance management in curated databases
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
ORCHESTRA: facilitating collaborative data sharing
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Provenance-aware storage systems
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
An annotation management system for relational databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Graphs-at-a-time: query language and access methods for graph databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
On the expressiveness of implicit provenance in query and update languages
ACM Transactions on Database Systems (TODS)
A framework for fine-grained data integration and curation, with provenance, in a dataspace
TAPP'09 First workshop on on Theory and practice of provenance
A provenance model for manually curated data
IPAW'06 Proceedings of the 2006 international conference on Provenance and Annotation of Data
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Writing relational database queries over current provenance databases can be complex and error-prone because application data is typically mixed with provenance data, because queries may require recursion, and because the form in which provenance is maintained requires procedural parsing not easily framed in query syntax. As a result, it is often difficult to write queries that select (rows or columns of) data based on provenance. In this paper, we contribute a conceptual model and a predicate language for use in relational algebra that allows the user to write simple, nonrecursive queries to select data and attributes based on provenance. Our model also includes novel data and provenance features, including multi-valued attributes, that are useful for data curation settings. We show that our predicate language supports a broad class of queries that select application data based on provenance. We also show how selection of data with our language extensions can be emulated with an existing graph database system and its associated query language.