Stratifying semantic data for citation and trust: An introduction to RDFDF

Dario De Nart; Dante Degl’Innocenti; Marco Peressotti; Carlo Tasso

doi:10.1007/978-3-319-56300-8_10

Stratifying semantic data for citation and trust: An introduction to RDFDF

Dario De Nart, Dante Degl’Innocenti, Marco Peressotti, Carlo Tasso^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

In this paper we analyse the functional requirements of linked data citation and identify a minimal set of operations and primitives needed to realise such task. Citing linked data implies solving a series of data provenance issues and finding a way to identify data subsets. Those two tasks can be handled defining a simple type system inside data and verifying it with a type checker, which is significantly less complex than interpreting reified RDF statements and can be implemented in a non data invasive way. Finally we suggest that data citation should be handled outside of the data, and propose a simple language to describe RDF documents where separation between data and metainformation is explicitly specified.

Original language	English
Title of host publication	Digital Libraries and Multimedia Archives - 12th Italian Research Conference on Digital Libraries, IRCDL 2016, Revised Selected Papers
Publisher	Springer
Publication date	8. Apr 2017
Pages	104-111
ISBN (Print)	978-3-319-56299-5
ISBN (Electronic)	978-3-319-56300-8
DOIs	https://doi.org/10.1007/978-3-319-56300-8_10
Publication status	Published - 8. Apr 2017
Externally published	Yes
Event	12th Italian Research Conference on Digital Libraries, IRCDL 2016 - Florence, Italy Duration: 4. Feb 2016 → 5. Feb 2016

Conference

Conference	12th Italian Research Conference on Digital Libraries, IRCDL 2016
Country/Territory	Italy
City	Florence
Period	04/02/2016 → 05/02/2016
Sponsor	MICC Center of Excellence, University of Florence

Series	Communications in Computer and Information Science
Volume	701
ISSN	1865-0929

Keywords

Data citation
Data trust
RDF
Semantic publishing
Semantic web
Knowledge representation
Digital Libraries

Documents & Links

10.1007/978-3-319-56300-8_10

1 Journal article

Well-Stratified Linked Data for Well-Behaved Data Citation
De Nart, D., Degl’Innocenti, D. & Peressotti, M., 2016, In: Bulletin of IEEE Technical Committee on Digital Libraries. 12, 1, p. 16-26 2.
Research output: Contribution to journal › Journal article › Research › peer-review

Cite this

De Nart, D., Degl’Innocenti, D., Peressotti, M., & Tasso, C. (2017). Stratifying semantic data for citation and trust: An introduction to RDFDF. In Digital Libraries and Multimedia Archives - 12th Italian Research Conference on Digital Libraries, IRCDL 2016, Revised Selected Papers (pp. 104-111). Springer. Communications in Computer and Information Science Vol. 701 https://doi.org/10.1007/978-3-319-56300-8_10

De Nart, Dario ; Degl’Innocenti, Dante ; Peressotti, Marco et al. / Stratifying semantic data for citation and trust : An introduction to RDFDF. Digital Libraries and Multimedia Archives - 12th Italian Research Conference on Digital Libraries, IRCDL 2016, Revised Selected Papers. Springer, 2017. pp. 104-111 (Communications in Computer and Information Science, Vol. 701).

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title = "Stratifying semantic data for citation and trust: An introduction to RDFDF",

abstract = "In this paper we analyse the functional requirements of linked data citation and identify a minimal set of operations and primitives needed to realise such task. Citing linked data implies solving a series of data provenance issues and finding a way to identify data subsets. Those two tasks can be handled defining a simple type system inside data and verifying it with a type checker, which is significantly less complex than interpreting reified RDF statements and can be implemented in a non data invasive way. Finally we suggest that data citation should be handled outside of the data, and propose a simple language to describe RDF documents where separation between data and metainformation is explicitly specified.",

keywords = "Data citation, Data trust, RDF, Semantic publishing, Semantic web, Knowledge representation, Digital Libraries",

author = "{De Nart}, Dario and Dante Degl{\textquoteright}Innocenti and Marco Peressotti and Carlo Tasso",

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De Nart, D, Degl’Innocenti, D, Peressotti, M & Tasso, C 2017, Stratifying semantic data for citation and trust: An introduction to RDFDF. in Digital Libraries and Multimedia Archives - 12th Italian Research Conference on Digital Libraries, IRCDL 2016, Revised Selected Papers. Springer, Communications in Computer and Information Science, vol. 701, pp. 104-111, 12th Italian Research Conference on Digital Libraries, IRCDL 2016, Florence, Italy, 04/02/2016. https://doi.org/10.1007/978-3-319-56300-8_10

Stratifying semantic data for citation and trust : An introduction to RDFDF. / De Nart, Dario; Degl’Innocenti, Dante; Peressotti, Marco et al.

Digital Libraries and Multimedia Archives - 12th Italian Research Conference on Digital Libraries, IRCDL 2016, Revised Selected Papers. Springer, 2017. p. 104-111 (Communications in Computer and Information Science, Vol. 701).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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T1 - Stratifying semantic data for citation and trust

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AU - Degl’Innocenti, Dante

AU - Peressotti, Marco

AU - Tasso, Carlo

PY - 2017/4/8

Y1 - 2017/4/8

N2 - In this paper we analyse the functional requirements of linked data citation and identify a minimal set of operations and primitives needed to realise such task. Citing linked data implies solving a series of data provenance issues and finding a way to identify data subsets. Those two tasks can be handled defining a simple type system inside data and verifying it with a type checker, which is significantly less complex than interpreting reified RDF statements and can be implemented in a non data invasive way. Finally we suggest that data citation should be handled outside of the data, and propose a simple language to describe RDF documents where separation between data and metainformation is explicitly specified.

AB - In this paper we analyse the functional requirements of linked data citation and identify a minimal set of operations and primitives needed to realise such task. Citing linked data implies solving a series of data provenance issues and finding a way to identify data subsets. Those two tasks can be handled defining a simple type system inside data and verifying it with a type checker, which is significantly less complex than interpreting reified RDF statements and can be implemented in a non data invasive way. Finally we suggest that data citation should be handled outside of the data, and propose a simple language to describe RDF documents where separation between data and metainformation is explicitly specified.

KW - Data citation

KW - Data trust

KW - RDF

KW - Semantic publishing

KW - Semantic web

KW - Knowledge representation

KW - Digital Libraries

U2 - 10.1007/978-3-319-56300-8_10

DO - 10.1007/978-3-319-56300-8_10

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AN - SCOPUS:85018697973

SN - 978-3-319-56299-5

T3 - Communications in Computer and Information Science

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De Nart D, Degl’Innocenti D, Peressotti M, Tasso C. Stratifying semantic data for citation and trust: An introduction to RDFDF. In Digital Libraries and Multimedia Archives - 12th Italian Research Conference on Digital Libraries, IRCDL 2016, Revised Selected Papers. Springer. 2017. p. 104-111. (Communications in Computer and Information Science, Vol. 701). doi: 10.1007/978-3-319-56300-8_10

Stratifying semantic data for citation and trust: An introduction to RDFDF

Abstract

Conference

Keywords

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Related Research Output

Well-Stratified Linked Data for Well-Behaved Data Citation

Cite this