SQL:2003 has been published

Eisenberg, Andrew; Melton, Jim; Kulkarni, Krishna; Michels, Jan-Eike; Zemke, Fred

doi:10.1145/974121.974142

Cited by 84 publications

(46 citation statements)

References 1 publication

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“…To be aligned with these extensions, we present in this work, a methodology that translates an XMLbased DTD into an OR schema based on the structured query language (SQL):2003 standards, named also SQL4 [6][7][8][9]13]. This methodology is based on a mapping function defined between XML and OR models.…”

Section: Related Workmentioning

confidence: 99%

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Transforming XML into Object-Relational Schema

Machkour¹,

Afdel²

2016

IOSR

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Section: Related Workmentioning

confidence: 99%

“…These notations help us to formalize the steps of the transformation and make it automatic. The concepts of the OR model include [8,9,13]:…”

Section: Concepts and Notationsmentioning

confidence: 99%

Transforming XML into Object-Relational Schema

Machkour¹,

Afdel²

2016

IOSR

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“…Ease of Use: Queries in the OSNDB system conform to the SQL:2003 standard [9]. No new constructs needs to be introduced.…”

Section: Query Platformmentioning

confidence: 99%

A Spatio-Temporal Approach to the Discovery of Online Social Trends

Achrekar

Zheng

et al. 2011

Combinatorial Optimization and Applications

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Abstract. Online social networks (OSNs) have become popular platforms for people to interact with each other in the cyber space. Users use OSNs to talk about their daily activities, mood, health status, sports events, travel experiences, political campaigns, entertainment events, and commercial products, among other things. Conversations between users on an OSN site could reflect the current social trends that are of great interest and importance for individuals, businesses, and government agencies alike. In this paper we design and develop a comprehensive system to collect, store, query, and analyze OSN data for effective discovery of online social trends. Our system consists of three parts: (1) an OSN data collection engine; (2) a spatio-temporal database for storing, indexing, and querying data; and (3) a set of analytical tools for online social trend discovery. We demonstrate the effectiveness of our system using a recent result of predicting seasonal flu trends using Twitter data.

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“…Tables can be created via graphical interfaces or command line tools, and loaded from text files. The database supports the Structured Query Language (SQL; Eisenberg, Kulkarni, Melton, Michels, & Zemke, 2004) that is used to specify what information is to be pulled from the database. Access to the database is typically achieved via Internet protocols, so that remote data can be accessed given proper security permissions, but for development purposes, a command line mode is also available.…”

Section: Server Implementation-mentioning

confidence: 99%

Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing

et al. 2008

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The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data.

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SQL:2003 has been published

Cited by 84 publications

References 1 publication

Transforming XML into Object-Relational Schema

Transforming XML into Object-Relational Schema

A Spatio-Temporal Approach to the Discovery of Online Social Trends

Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing

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