Deriving an emergent relational schema from RDF data

Minh Duc Pham; Linnea Passing; Orri Erling; Peter Boncz

doi:10.1145/2736277.2741121

Deriving an emergent relational schema from RDF data

Minh Duc Pham, Linnea Passing, Orri Erling, Peter Boncz

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

Abstract

We motivate and describe techniques that allow to detect an "emergent" relational schema from RDF data. We show that on a wide variety of datasets, the found structure explains well over 90% of the RDF triples. Further, we also describe technical solutions to the semantic challenge to give short names that humans find logical to these emergent tables, columns and relationships between tables. Our techniques can be exploited in many ways, e.g., to improve the efficiency of SPARQL systems, or to use existing SQL-based applications on top of any RDF dataset using a RDBMS.

Original language	English
Title of host publication	WWW 2015 - Proceedings of the 24th International Conference on World Wide Web
Publisher	Association for Computing Machinery, Inc
Pages	864-874
Number of pages	11
ISBN (Electronic)	9781450334693
DOIs	https://doi.org/10.1145/2736277.2741121
Publication status	Published - 18 May 2015
Event	24th International Conference on World Wide Web, WWW 2015 - Florence, Italy Duration: 18 May 2015 → 22 May 2015

Conference

Conference	24th International Conference on World Wide Web, WWW 2015
Country/Territory	Italy
City	Florence
Period	18/05/15 → 22/05/15

Keywords

RDF
Relational schema
Structure recognition

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10.1145/2736277.2741121

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@inproceedings{d48a78a529e14a778429727d45d18381,

title = "Deriving an emergent relational schema from RDF data",

abstract = "We motivate and describe techniques that allow to detect an {"}emergent{"} relational schema from RDF data. We show that on a wide variety of datasets, the found structure explains well over 90% of the RDF triples. Further, we also describe technical solutions to the semantic challenge to give short names that humans find logical to these emergent tables, columns and relationships between tables. Our techniques can be exploited in many ways, e.g., to improve the efficiency of SPARQL systems, or to use existing SQL-based applications on top of any RDF dataset using a RDBMS.",

keywords = "RDF, Relational schema, Structure recognition",

author = "Pham, {Minh Duc} and Linnea Passing and Orri Erling and Peter Boncz",

year = "2015",

month = may,

day = "18",

doi = "10.1145/2736277.2741121",

language = "English",

pages = "864--874",

booktitle = "WWW 2015 - Proceedings of the 24th International Conference on World Wide Web",

publisher = "Association for Computing Machinery, Inc",

note = "24th International Conference on World Wide Web, WWW 2015 ; Conference date: 18-05-2015 Through 22-05-2015",

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TY - GEN

T1 - Deriving an emergent relational schema from RDF data

AU - Pham, Minh Duc

AU - Passing, Linnea

AU - Erling, Orri

AU - Boncz, Peter

PY - 2015/5/18

Y1 - 2015/5/18

N2 - We motivate and describe techniques that allow to detect an "emergent" relational schema from RDF data. We show that on a wide variety of datasets, the found structure explains well over 90% of the RDF triples. Further, we also describe technical solutions to the semantic challenge to give short names that humans find logical to these emergent tables, columns and relationships between tables. Our techniques can be exploited in many ways, e.g., to improve the efficiency of SPARQL systems, or to use existing SQL-based applications on top of any RDF dataset using a RDBMS.

AB - We motivate and describe techniques that allow to detect an "emergent" relational schema from RDF data. We show that on a wide variety of datasets, the found structure explains well over 90% of the RDF triples. Further, we also describe technical solutions to the semantic challenge to give short names that humans find logical to these emergent tables, columns and relationships between tables. Our techniques can be exploited in many ways, e.g., to improve the efficiency of SPARQL systems, or to use existing SQL-based applications on top of any RDF dataset using a RDBMS.

KW - RDF

KW - Relational schema

KW - Structure recognition

UR - http://www.scopus.com/inward/record.url?scp=84968830703&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84968830703&partnerID=8YFLogxK

U2 - 10.1145/2736277.2741121

DO - 10.1145/2736277.2741121

M3 - Conference contribution

AN - SCOPUS:84968830703

SP - 864

EP - 874

BT - WWW 2015 - Proceedings of the 24th International Conference on World Wide Web

PB - Association for Computing Machinery, Inc

T2 - 24th International Conference on World Wide Web, WWW 2015

Y2 - 18 May 2015 through 22 May 2015

ER -

Deriving an emergent relational schema from RDF data

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