Constructing Experts Profiles from Linked Open Data

Inspired from Linked Open Data (LOD) initiative, Latif et al. have developed a tool which can establish links between authors of digital journals with relevant semantic resources available in LOD [1]. The proposed system is able to disambiguate authors and can: 1) locate, 2) retrieve, and 3) structure the relevant semantic resources. Furthermore, the system constructs comprehensive aspect oriented authors’ profiles from heterogeneous datasets of LOD on the fly. They investigated the potentials of such an approach on a digital journal known as Journal of Universal Computer Science (J.UCS). It is their strong belief that this kind of applications can motivate researchers and developers to investigate different application areas where Linked Open Data can contribute, bring added value, and can take the idea of open access further.

Because of the strong resemblance to our application, some interesting aspects of their approach will be used in this project.

The emergence of many semantically rich and structured datasets from Linked Open Data movement (LOD) can facilitate in more controlled search and fruitful results. Latif et al. employed 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.

Latif et al. designed a system divided in to three layers which interact with each other to make the system operational: Expertise Calculation, Visualization, Locating and Construction of Expert Profile. In their paper [2], they proposed and implemented an automatic technique for discovering this information. The system uses Linked Data paradigm for acquiring semantically rich information. The proposed set of heuristics was able to disambiguate experts, in acquiring relevant information, and structuring the information to produce a coherent view of the expert.

Their system has been implemented for a journal such as Journal of Universal Computer Science (J.UCS). The proposed system is useful for the J.UCS administration to assign reviewing duties by presenting a comprehensive expert profile. The proposed system is useful for the J.UCS administration to assign reviewing duties by presenting a comprehensive expert profile.

The linking as proposed by the authors is helpful for different scenarios e.g.: for users who are searching research collaborators, for journal administration who want to assign new reviewers and for users who want to explore experts to seek guidance. A comprehensive profile of an author was structured and visualized at one place providing various opportunities for collaborations. This is helpful in getting deep insights of author’s work, personal and professional life.

We will base our user interface on their automatic method of expert profile construction.



  1. Latif A., Afzal M.T., Helic D., Tochtermann K., Hermann Maurer H., Discovery and Construction of Authors’ Profile from Linked Data (A case study for Open Digital Journal). (2010)
  2. Latif A., Afzal M.T., Tochtermann K., Constructing experts profiles from Linked Open Data. Emerging Technologies. (ICET)



About laurensdv
Computer Science Student, interested in creating more innovating user experiences for information access. Fond of travelling around Europe!

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