The semantic web: From representation to realization

Kristinn R. Thórisson; Nova Spivack; James M. Wissner

doi:10.1007/978-3-642-17155-0_5

The semantic web: From representation to realization

Kristinn R. Thórisson, Nova Spivack, James M. Wissner

Department of Computer Science

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

2 Citations (Scopus)

Abstract

A semantically-linked web of electronic information - the Semantic Web - promises numerous benefits including increased precision in automated information sorting, searching, organizing and summarizing. Realizing this requires significantly more reliable meta-information than is readily available today. It also requires a better way to represent information that supports unified management of diverse data and diverse Manipulation methods: from basic keywords to various types of artificial intelligence, to the highest level of intelligent manipulation - the human mind. How this is best done is far from obvious. Relying solely on hand-crafted annotation and ontologies, or solely on artificial intelligence techniques, seems less likely for success than a combination of the two. In this paper describe an integrated, complete solution to these challenges that has already been implemented and tested with hundreds of thousands of users. It is based on an ontological representational level we call SemCards that combines ontological rigour with flexible user interface constructs. SemCards are machine- and human-readable digital entities that allow non-experts to create and use semantic content, while empowering machines to better assist and participate in the process. SemCards enable users to easily create semantically-grounded data that in turn acts as examples for automation processes, creating a positive iterative feedback loop of metadata creation and refinement between user and machine. They provide a holistic solution to the Semantic Web, supporting powerful management of the full lifecycle of data, including its creation, retrieval, classification, sorting and sharing. We have implemented the SemCard technology on the semantic Web site Twine.com, showing that the technology is indeed versatile and scalable. Here we present the key ideas behind SemCards and describe the initial implementation of the technology.

Original language	English
Title of host publication	Transactions on Computational Collective Intelligence II
Editors	Ngoc Thanh Nguyen, Ryszard Kowalczyk
Pages	90-107
Number of pages	18
DOIs	https://doi.org/10.1007/978-3-642-17155-0_5
Publication status	Published - 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6450 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Funding Information:
Acknowledgments. The work was supported by Radar Networks, Inc., by Reykjavik University, Iceland, and by the School of Computer Science at Reykjavik University. The authors would like to thank the Twine team for the implementation of the SemCard technology on Twine.com, as well as the funders of Radar, Vulcan Ventures Inc., Leapfrog Ventures Inc. and the angel investors.

Other keywords

Human-Machine Collaboration
Knowledge Management
Metadata
Ontologies
Semantic Web
SemCards
Twine.com
User Interface

Access to Document

10.1007/978-3-642-17155-0_5

Cite this

Thórisson, K. R., Spivack, N., & Wissner, J. M. (2010). The semantic web: From representation to realization. In N. T. Nguyen, & R. Kowalczyk (Eds.), Transactions on Computational Collective Intelligence II (pp. 90-107). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6450 LNCS). https://doi.org/10.1007/978-3-642-17155-0_5

Thórisson, Kristinn R. ; Spivack, Nova ; Wissner, James M. / The semantic web : From representation to realization. Transactions on Computational Collective Intelligence II. editor / Ngoc Thanh Nguyen ; Ryszard Kowalczyk. 2010. pp. 90-107 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{c58f4186ed1f44538d80a16b2ee28853,

title = "The semantic web: From representation to realization",

abstract = "A semantically-linked web of electronic information - the Semantic Web - promises numerous benefits including increased precision in automated information sorting, searching, organizing and summarizing. Realizing this requires significantly more reliable meta-information than is readily available today. It also requires a better way to represent information that supports unified management of diverse data and diverse Manipulation methods: from basic keywords to various types of artificial intelligence, to the highest level of intelligent manipulation - the human mind. How this is best done is far from obvious. Relying solely on hand-crafted annotation and ontologies, or solely on artificial intelligence techniques, seems less likely for success than a combination of the two. In this paper describe an integrated, complete solution to these challenges that has already been implemented and tested with hundreds of thousands of users. It is based on an ontological representational level we call SemCards that combines ontological rigour with flexible user interface constructs. SemCards are machine- and human-readable digital entities that allow non-experts to create and use semantic content, while empowering machines to better assist and participate in the process. SemCards enable users to easily create semantically-grounded data that in turn acts as examples for automation processes, creating a positive iterative feedback loop of metadata creation and refinement between user and machine. They provide a holistic solution to the Semantic Web, supporting powerful management of the full lifecycle of data, including its creation, retrieval, classification, sorting and sharing. We have implemented the SemCard technology on the semantic Web site Twine.com, showing that the technology is indeed versatile and scalable. Here we present the key ideas behind SemCards and describe the initial implementation of the technology.",

keywords = "Human-Machine Collaboration, Knowledge Management, Metadata, Ontologies, Semantic Web, SemCards, Twine.com, User Interface",

author = "Th{\'o}risson, {Kristinn R.} and Nova Spivack and Wissner, {James M.}",

note = "Funding Information: Acknowledgments. The work was supported by Radar Networks, Inc., by Reykjavik University, Iceland, and by the School of Computer Science at Reykjavik University. The authors would like to thank the Twine team for the implementation of the SemCard technology on Twine.com, as well as the funders of Radar, Vulcan Ventures Inc., Leapfrog Ventures Inc. and the angel investors.",

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Thórisson, KR, Spivack, N & Wissner, JM 2010, The semantic web: From representation to realization. in NT Nguyen & R Kowalczyk (eds), Transactions on Computational Collective Intelligence II. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6450 LNCS, pp. 90-107. https://doi.org/10.1007/978-3-642-17155-0_5

The semantic web: From representation to realization. / Thórisson, Kristinn R.; Spivack, Nova; Wissner, James M.
Transactions on Computational Collective Intelligence II. ed. / Ngoc Thanh Nguyen; Ryszard Kowalczyk. 2010. p. 90-107 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6450 LNCS).

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

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N1 - Funding Information: Acknowledgments. The work was supported by Radar Networks, Inc., by Reykjavik University, Iceland, and by the School of Computer Science at Reykjavik University. The authors would like to thank the Twine team for the implementation of the SemCard technology on Twine.com, as well as the funders of Radar, Vulcan Ventures Inc., Leapfrog Ventures Inc. and the angel investors.

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N2 - A semantically-linked web of electronic information - the Semantic Web - promises numerous benefits including increased precision in automated information sorting, searching, organizing and summarizing. Realizing this requires significantly more reliable meta-information than is readily available today. It also requires a better way to represent information that supports unified management of diverse data and diverse Manipulation methods: from basic keywords to various types of artificial intelligence, to the highest level of intelligent manipulation - the human mind. How this is best done is far from obvious. Relying solely on hand-crafted annotation and ontologies, or solely on artificial intelligence techniques, seems less likely for success than a combination of the two. In this paper describe an integrated, complete solution to these challenges that has already been implemented and tested with hundreds of thousands of users. It is based on an ontological representational level we call SemCards that combines ontological rigour with flexible user interface constructs. SemCards are machine- and human-readable digital entities that allow non-experts to create and use semantic content, while empowering machines to better assist and participate in the process. SemCards enable users to easily create semantically-grounded data that in turn acts as examples for automation processes, creating a positive iterative feedback loop of metadata creation and refinement between user and machine. They provide a holistic solution to the Semantic Web, supporting powerful management of the full lifecycle of data, including its creation, retrieval, classification, sorting and sharing. We have implemented the SemCard technology on the semantic Web site Twine.com, showing that the technology is indeed versatile and scalable. Here we present the key ideas behind SemCards and describe the initial implementation of the technology.

AB - A semantically-linked web of electronic information - the Semantic Web - promises numerous benefits including increased precision in automated information sorting, searching, organizing and summarizing. Realizing this requires significantly more reliable meta-information than is readily available today. It also requires a better way to represent information that supports unified management of diverse data and diverse Manipulation methods: from basic keywords to various types of artificial intelligence, to the highest level of intelligent manipulation - the human mind. How this is best done is far from obvious. Relying solely on hand-crafted annotation and ontologies, or solely on artificial intelligence techniques, seems less likely for success than a combination of the two. In this paper describe an integrated, complete solution to these challenges that has already been implemented and tested with hundreds of thousands of users. It is based on an ontological representational level we call SemCards that combines ontological rigour with flexible user interface constructs. SemCards are machine- and human-readable digital entities that allow non-experts to create and use semantic content, while empowering machines to better assist and participate in the process. SemCards enable users to easily create semantically-grounded data that in turn acts as examples for automation processes, creating a positive iterative feedback loop of metadata creation and refinement between user and machine. They provide a holistic solution to the Semantic Web, supporting powerful management of the full lifecycle of data, including its creation, retrieval, classification, sorting and sharing. We have implemented the SemCard technology on the semantic Web site Twine.com, showing that the technology is indeed versatile and scalable. Here we present the key ideas behind SemCards and describe the initial implementation of the technology.

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Thórisson KR, Spivack N, Wissner JM. The semantic web: From representation to realization. In Nguyen NT, Kowalczyk R, editors, Transactions on Computational Collective Intelligence II. 2010. p. 90-107. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-17155-0_5

The semantic web: From representation to realization

Abstract

Publication series

Bibliographical note

Other keywords

Access to Document

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Cite this