A New Framework for the Citation Indexing Paradigm

A new citation indexing paradigm is proposed: the cascading citation indexing framework (c2IF, for short). It improves the way research publications are assessed for their impact in promoting science and technology. Given a collection of articles and their citation graph, citations are considered at the (article, author) level. Each one article is uniquely identified by means of the Digital Object Identifier (DOI, http://www.doi.org). To identify each one author uniquely, a Universal Author Identifier (UAI) scheme is established. In addition to the citations directly made to a given (article, author) pair, citation paths that target each one citing article are also considered. The granularity of the paradigm is further increased by introducing the concept of the chord, whereby a citation path of length one co-exists with paths of length two or higher, involving the same source- and target- articles. The c2IF output emerges in the form of a medal standings table, analogous to the one that ranks teams at athletic events: when two (article, author) pairs receive the same number of (direct) citations, the one that is cited by more popular articles (i.e. articles that comprise targets to a larger number of paths in the citation graph), is assigned a higher rank value

cc-IFF: A Cascading Citations Impact Factor Framework for the Automatic Ranking of Research Publications

The present item comprises an amended (post-print) version of: D.A. Dervos and T. Kalkanis, cc-IFF: A Cascading Citations Impact Factor Framework for the Automatic Ranking of Research Publications, Third IEEE International Workshop on Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Proceedings pp. 668-673, Sofia, Bulgaria, September 5-7, 2005A new framework is proposed for the calculation of impact factor ratings of research publications. Given a collection of research articles, the corresponding citations graph is constructed in the form of a relational table. The impact value is considered at the article level, and is calculated by considering not only the citations made directly to an article, but also citations made to the corresponding citing article(s). In this respect, an improved algorithm is utilized, namely one that traverses all the threads in the citations graph, in an attempt to improve the degree of fairness in assigning credit for the impact value of each one article. When two articles have an equal number of (direct) citations, the one that has triggered more research activity (i.e. its citing articles attract a larger number of citations at subsequent levels in the citations graph) is assigned a higher impact value and, consequently, is ranked to be better

A Common Sense Approach to Defining Data, Information, and Metadata

This is a presentation (~25 slides) made at ISKO 2006 in Vienna based on the paper (same title) published in the Proceedings of the Ninth International ISKO 2006 Conference, Vienna, Edited by Swertz, C. Berlin: Ergon, 2006

A Common Sense Approach to Defining Data, Information, and Metadata

This is a preprint of a paper published. Dervos, D. and Coleman, A. (2006). A Common Sense Approach to Defining Data, Information and Metadata. Advances in Knowledge Organization: Proceedings of the Ninth International Society for Knowledge Organization 2006 Conference, Vienna. June 2006, Edited by G. Budin and C. Swertz. Berlin: Ergon. Abstract: Many competing definitions for the terms data, information, metadata, and knowledge can be traced in the library and information science literature. The lack of a clear consensus in the way reference is made to the corresponding fundamental concepts is intensified if one considers additional disciplinary perspectives, e.g. database technology, data mining, etc. In the present paper, we use a common sense approach borrowed from the data mining community, which has successfully solved many data processing problems, to selectively survey the literature, and define these terms in a way that can advance the interdisciplinary development of information systems

A New Framework for the Citation Indexing Paradigm

A new citation indexing paradigm is proposed: the cascading citation indexing framework (c 2 IF, for short). It improves the way research publications are assessed for their impact in promoting science and technology. Given a collection of articles and their citation graph, citations are considered at the (article, author) level. Each one article is uniquely identified b

The Universal Author Identifier System (UAI_Sys)

One common problem in the scientific research literature is that each one author cannot easily be identified uniquely. The problem arises when there are authors with identical names, authors who have changed their name(s) in the course of time, and authors whose names appear in alternative versions (for example: Jaakko Hyvärinen, and J. P. Hyvärinen) across the publications they have (co-) authored. The issue becomes more of a problem when data analysis utilizing author names is to be conducted, for example: in citation analysis. In this paper we introduce the Universal Author Identifier system, codenamed UAI_Sys. The system is web based and publicly available, enabling each one author to register/update his/her own metadata, plus acquire a unique identifier (UAI code), ensuring name disambiguation. As soon as UAI_Sys becomes accepted and enjoys worldwide use, selected author metadata will become globally available to all interested parties. Care is taken so that UAI_Sys comprises more than just a database for storing and handling author identifiers. Provision is taken for the system to incorporate web services facilitating communication with third party applications, thus expanding the possibilities for web based co-functionality. Last but not least, the system supports role-based access and management (i.e. different user roles for authors, librarians, publishers, and administrators) for efficient and effective information dissemination and management, promoting research and collaboration. UAI_Sys is being designed/developed along the lines of the Cascading Citations Analysis Project (C-CAP) which is co-funded by the Alexander Technology Educational Institute (ATEI), and the University of Macedonia (UoM)

The Universal Author Identifier System (UAI_Sys)

One common problem in the scientific research literature is that each one author cannot easily be identified uniquely. The problem arises when there are authors with identical names, authors who have changed their name(s) in the course of time, and authors whose names appear in alternative versions (for example: Jaakko Hyvärinen, and J. P. Hyvärinen) across the publications they have (co-) authored. The issue becomes more of a problem when data analysis utilizing author names is to be conducted, for example: in citation analysis. In this paper we introduce the Universal Author Identifier system, codenamed UAI_Sys. The system is web based and publicly available, enabling each one author to register/update his/her own metadata, plus acquire a unique identifier (UAI code), ensuring name disambiguation. As soon as UAI_Sys becomes accepted and enjoys worldwide use, selected author metadata will become globally available to all interested parties. Care is taken so that UAI_Sys comprises more than just a database for storing and handling author identifiers. Provision i