Experimenting with temporal relational databases

Goralwalla, Iqbal A.; Tansel, Abudullah U.; Özsu, M. Tamer

doi:10.1145/221270.221597

Cited by 11 publications

(8 citation statements)

References 22 publications

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“…Assumptions have been made in the literature about the ease of use of temporal extensions [16]. Conceptual models have been presented which are claimed to be more intuitive to the user [17,5].…”

Section: Motivationmentioning

confidence: 99%

“…Designers of temporal extensions have only built implementations that support their own extension and have used them primarily to demonstrate feasibility [14] and to evaluate their extension in isolation [5]. In addition, gaining access to many of these extensions by independent researchers is not possible and, as the interfaces inevitably differ anyway, comparative analysis of extensions using their own implementation is not possible as the difference in the interface would invalidate the result [2,21].…”

Section: Motivationmentioning

confidence: 99%

See 1 more Smart Citation

ProSQL: A Prototyping Tool for SQL Temporal Language Extensions

Green

Johnson

2003

Lecture Notes in Computer Science

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Abstract. This paper describes ProSQL, a novel prototyping tool to support the development of extensions to SQL. ProSQL provides a simple way to prototype the features of a proposed extension and thus provide a proof of concept. Further, it provides proposers and reviewers of extensions with a clearer view of their positive and negative features. The approach adopted has been to build a wrapper around an existing database management system, in this case Microsoft Access, and to provide a collection of interfaces with which a designer can define extensions to the basic relational database.

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Section: Motivationmentioning

confidence: 99%

Section: Motivationmentioning

confidence: 99%

ProSQL: A Prototyping Tool for SQL Temporal Language Extensions

Green

Johnson

2003

Lecture Notes in Computer Science

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“…The theory behind these languages and algebra is quite advanced, but only a few experimental implementations have been carried out [8]. While some aspects of this research are relevant to the proposed investigation, such as expressing of temporal intervals for querying, the emphasis on database states and their variance in time is not as relevant.…”

Section: Related Workmentioning

confidence: 99%

Supporting storage and retrieval of computer and human activity

Spiteri

Bates

1998

Proceedings of the 8th ACM SIGOPS European Workshop on Support for Composing Distributed Applications

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This paper describes the architecture we designed and constructed to support the storage and retrieval of human and computer activity. We collect information about activities occurring in the real physical world as well as information relating to activities occurring within a computer environment. Important information regarding such activities is digitally represented through paramertised asynchronous events, denoting, for example, workstation operations like manipulation of files and launching of applications, or tracking of users' physical movements, usage of the telephone system, taking books from the library, etc. Our past experience has demonstrated how using events as the glue to build distributed active systems simplifies the construction of complex applications, and enables legacy stand-alone components to be rapidly integated within a larger collaborative environment. Our motivation for storing events is that events can represent indexing points into activities and enable an activity to be reconstructed or replayed. This is particularly useful for capture of online collaboration, automated diary generation, memory recollection environments, and novel scenarios like visualisation and analysis of user mobility. We have designed and authored an event repository architecture that provides powerful search and retrieval facilities, enabling extraction of behaviour patterns, searching for simple and composite occurrences, and replay of stored sequences.

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“…The ability to model the time dimension is essential to many real-world applications, such as banking, inventory control, health-care, and geographical information systems [6,1,12].…”

Section: Temporal Data Modelmentioning

confidence: 99%

“…Temporal relational model can support either attribute timestamping or tuple timestamping [6]. In attribute timestamping, each attribute in a temporal relation has its own timestamp that represents the time interval for the validity of the attribute value.…”

Section: Temporal Data Modelmentioning

confidence: 99%