CAF-SIAL: Concept aggregation framework for structuring informational aspects of linked open data

Latif, Atif; Afzal, Muhammad; Saeed, Anwar Us; Hoefler, Patrick; Tochtermann, Klaus

doi:10.1109/ndt.2009.5272079

Cited by 10 publications

(9 citation statements)

References 7 publications

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“…In [1], we looked into ways to turn search keywords into URIs and applied the technique in a simplified end-user interface for accessing Linked Data. This approach was extended into CAF-SIAL, a proofof-concept application described in [2] and [3]. CAF-SIAL helped users to search information about concepts in the Linked Open Data cloud without having to know any of the mechanics of the Semantic Web.…”

Section: Approach and Research Methodologymentioning

confidence: 99%

Linked Data Interfaces for Non-expert Users

Hoefler

2013

The Semantic Web: Semantics and Big Data

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Abstract. Linked Data has become an essential part of the Semantic Web. A lot of Linked Data is already available in the Linked Open Data cloud, which keeps growing due to an influx of new data from research and open government activities. However, it is still quite difficult to access this wealth of semantically enriched data directly without having indepth knowledge about SPARQL and related semantic technologies. The presented dissertation explores Linked Data interfaces for non-expert users, especially keyword search as an entry point and tabular interfaces for filtering and exploration. It also looks at the value chain surrounding Linked Data and the possibilities that open up when people without a background in computer science can easily access Linked Data.

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Section: Approach and Research Methodologymentioning

confidence: 99%

Linked Data Interfaces for Non-expert Users

Hoefler

2013

The Semantic Web: Semantics and Big Data

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“…In this case study [9], authors of open digital journal dataset was interlinked with the DBpedia by extending CAF-SIAL (Concept Aggregation Framework for Structuring Informational Aspects of Linked Open Data) application 7 . It is a proof of concept linked data application which finds and harvests person's relevant information from the LOD cloud [20]. Moreover, this information is organized and presented in informational aspect of person (personal, professional, educational and social) in a profile.…”

Section: Interlinking Case Studiesmentioning

confidence: 99%

Exploring Scientific Publication and Cross Domain Linked Dataset for Similarity - A Case Study

Latif¹,

Tochtermann²

2013

IJACT

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“…[3] This system is named as CAF-SIAL (Concept Aggregation Framework for Structuring Informational Aspects of Linked Open Data) [7]. CAF-SIAL is a proof of concept application to discover and present informational aspect of resource (Person) from LOD.…”

Section: Related Workmentioning

confidence: 99%

“…To locate intended resources URI, we have already presented an intelligent Keyword-URI mapping technique [6]. To retrieve and structure information resources, an innovative Concept Aggregation Framework [7] was developed. To present a comprehensive view of information, a user interface named as CAF-SIAL was developed 2 .…”

Section: Introductionmentioning

confidence: 99%

Constructing experts profiles from Linked Open Data

Latif

Afzal

Tochtermann

2010

2010 6th International Conference on Emerging Technologies (ICET)

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Identification and assignment of (potential) experts to subject field is an important task in various settings and environments. In scientific domain, the identification of experts is normally based on number of factors like: number of publications, citation record, and experience etc. However, the discovered experts cannot be assigned reviewing duties immediately. One also need further information about expert like the country, university, service record, contributions, honors, and name of conferences/journals where the discovered expert is already serving as editor/reviewer. To some extent, this information can be found from search engines using heuristics, by applying Natural Language Processing, and Machine Learning techniques. However, the emergence of many semantically rich and structured datasets from Linked Open Data movement (LOD) can facilitate in more controlled search and fruitful results. This paper employs an automatic technique to find the required information about experts using LOD dataset. The expert profile is discovered, aggregated, clustered, structured, and visualized to the administration of peer-review system. The system has been implemented for an electronic journal such as Journal of Universal Computer Science (J.UCS). The proposed system facilitates J.UCS administration to find potential reviewers for scientific papers to assign reviewing duties and to call new editors for computer science topics.

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CAF-SIAL: Concept aggregation framework for structuring informational aspects of linked open data

Abstract: Linked Open Data (LOD) is becoming an essential part of the Semantic

Cited by 10 publications

References 7 publications

Linked Data Interfaces for Non-expert Users

Linked Data Interfaces for Non-expert Users

Exploring Scientific Publication and Cross Domain Linked Dataset for Similarity - A Case Study

Constructing experts profiles from Linked Open Data

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