Representing and querying data transformations

Yannis Velegrakis; Renée J. Miller; John Mylopoulos

doi:10.1109/ICDE.2005.123

Representing and querying data transformations

Yannis Velegrakis^*, Renée J. Miller, John Mylopoulos

^*Corresponding author for this work

Sub Data Intensive Systems

University of Toronto

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Modern information systems often store data that has been transformed and integrated from a variety of sources. This integration may obscure the original source semantics of data items. For many tasks, it is important to be able to determine not only where data items originated, but also why they appear in the integration as they do and through what transformation they were derived. This problem is known as data provenance. In this work, we consider data provenance at the schema and mapping level. In particular, we consider how to answer questions such as "what schema elements in the source(s) contributed to this value", or "through what transformations or mappings was this value derived?" Towards this end, we elevate schemas and mappings to first-class citizens that are stored in a repository and are associated with the actual data values. An extended query language, called MXQL, is also developed that allows meta-data to be queried as regular data and we describe its implementation. scenario.

Original language	English
Title of host publication	Proceedings - 21st International Conference on Data Engineering, ICDE 2005
Pages	81-92
Number of pages	12
DOIs	https://doi.org/10.1109/ICDE.2005.123
Publication status	Published - 12 Dec 2005
Event	21st International Conference on Data Engineering, ICDE 2005 - Tokyo, Japan Duration: 5 Apr 2005 → 8 Apr 2005

Conference

Conference	21st International Conference on Data Engineering, ICDE 2005
Country/Territory	Japan
City	Tokyo
Period	5/04/05 → 8/04/05

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10.1109/ICDE.2005.123

Cite this

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title = "Representing and querying data transformations",

abstract = "Modern information systems often store data that has been transformed and integrated from a variety of sources. This integration may obscure the original source semantics of data items. For many tasks, it is important to be able to determine not only where data items originated, but also why they appear in the integration as they do and through what transformation they were derived. This problem is known as data provenance. In this work, we consider data provenance at the schema and mapping level. In particular, we consider how to answer questions such as {"}what schema elements in the source(s) contributed to this value{"}, or {"}through what transformations or mappings was this value derived?{"} Towards this end, we elevate schemas and mappings to first-class citizens that are stored in a repository and are associated with the actual data values. An extended query language, called MXQL, is also developed that allows meta-data to be queried as regular data and we describe its implementation. scenario.",

author = "Yannis Velegrakis and Miller, {Ren{\'e}e J.} and John Mylopoulos",

year = "2005",

month = dec,

day = "12",

doi = "10.1109/ICDE.2005.123",

language = "English",

isbn = "0769522858",

pages = "81--92",

booktitle = "Proceedings - 21st International Conference on Data Engineering, ICDE 2005",

note = "21st International Conference on Data Engineering, ICDE 2005 ; Conference date: 05-04-2005 Through 08-04-2005",

}

TY - GEN

T1 - Representing and querying data transformations

AU - Velegrakis, Yannis

AU - Miller, Renée J.

AU - Mylopoulos, John

PY - 2005/12/12

Y1 - 2005/12/12

N2 - Modern information systems often store data that has been transformed and integrated from a variety of sources. This integration may obscure the original source semantics of data items. For many tasks, it is important to be able to determine not only where data items originated, but also why they appear in the integration as they do and through what transformation they were derived. This problem is known as data provenance. In this work, we consider data provenance at the schema and mapping level. In particular, we consider how to answer questions such as "what schema elements in the source(s) contributed to this value", or "through what transformations or mappings was this value derived?" Towards this end, we elevate schemas and mappings to first-class citizens that are stored in a repository and are associated with the actual data values. An extended query language, called MXQL, is also developed that allows meta-data to be queried as regular data and we describe its implementation. scenario.

AB - Modern information systems often store data that has been transformed and integrated from a variety of sources. This integration may obscure the original source semantics of data items. For many tasks, it is important to be able to determine not only where data items originated, but also why they appear in the integration as they do and through what transformation they were derived. This problem is known as data provenance. In this work, we consider data provenance at the schema and mapping level. In particular, we consider how to answer questions such as "what schema elements in the source(s) contributed to this value", or "through what transformations or mappings was this value derived?" Towards this end, we elevate schemas and mappings to first-class citizens that are stored in a repository and are associated with the actual data values. An extended query language, called MXQL, is also developed that allows meta-data to be queried as regular data and we describe its implementation. scenario.

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U2 - 10.1109/ICDE.2005.123

DO - 10.1109/ICDE.2005.123

M3 - Conference contribution

AN - SCOPUS:28444467363

SN - 0769522858

SP - 81

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BT - Proceedings - 21st International Conference on Data Engineering, ICDE 2005

T2 - 21st International Conference on Data Engineering, ICDE 2005

Y2 - 5 April 2005 through 8 April 2005

ER -

Representing and querying data transformations

Abstract

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