BACKGROUND: A professional recognition mechanism is required to encourage expedited publishing of an adequate volume of 'fit-for-use' biodiversity data. As a component of such a recognition mechanism, we propose the development of the Data Usage Index (DUI) to demonstrate to data publishers that their efforts of creating biodiversity datasets have impact by being accessed and used by a wide spectrum of user communities. DISCUSSION: We propose and give examples of a range of 14 absolute and normalized biodiversity dataset usage indicators for the development of a DUI based on search events and dataset download instances. The DUI is proposed to include relative as well as species profile weighted comparative indicators. CONCLUSIONS: We believe that in addition to the recognition to the data publisher and all players involved in the data life cycle, a DUI will also provide much needed yet novel insight into how users use primary biodiversity data. A DUI consisting of a range of usage indicators obtained from the GBIF network and other relevant access points is within reach. The usage of biodiversity datasets leads to the development of a family of indicators in line with well known citation-based measurements of recognition.

BACKGROUND: Data are the evidentiary basis for scientific hypotheses, analyses and publication, for policy formation and for decision-making. They are essential to the evaluation and testing of results by peer scientists both present and future. There is broad consensus in the scientific and conservation communities that data should be freely, openly available in a sustained, persistent and secure way, and thus standards for 'free' and 'open' access to data have become well developed in recent years. The question of effective access to data remains highly problematic. DISCUSSION: Specifically with respect to scientific publishing, the ability to critically evaluate a published scientific hypothesis or scientific report is contingent on the examination, analysis, evaluation - and if feasible - on the re-generation of data on which conclusions are based. It is not coincidental that in the recent 'climategate' controversies, the quality and integrity of data and their analytical treatment were central to the debate. There is recent evidence that even when scientific data are requested for evaluation they may not be available. The history of dissemination of scientific results has been marked by paradigm shifts driven by the emergence of new technologies. In recent decades, the advance of computer-based technology linked to global communications networks has created the potential for broader and more consistent dissemination of scientific information and data. Yet, in this digital era, scientists and conservationists, organizations and institutions have often been slow to make data available. Community studies suggest that the withholding of data can be attributed to a lack of awareness, to a lack of technical capacity, to concerns that data should be withheld for reasons of perceived personal or organizational self interest, or to lack of adequate mechanisms for attribution. CONCLUSIONS: There is a clear need for institutionalization of a 'data publishing framework' that can address sociocultural, technical-infrastructural, policy, political and legal constraints, as well as addressing issues of sustainability and financial support. To address these aspects of a data publishing framework - a systematic, standard approach to the formal definition and public disclosure of data - in the context of biodiversity data, the Global Biodiversity Information Facility (GBIF, the single inter-governmental body most clearly mandated to undertake such an effort) convened a Data Publishing Framework Task Group. We conceive this data publishing framework as an environment conducive to ensure free and open access to world's biodiversity data. Here, we present the recommendations of that Task Group, which are intended to encourage free and open access to the worlds' biodiversity data.

BACKGROUND: Currently primary scientific data, especially that dealing with biodiversity, is neither easily discoverable nor accessible. Amongst several impediments, one is a lack of professional recognition of scientific data publishing efforts. A possible solution is establishment of a 'Data Publishing Framework' which would encourage and recognise investments and efforts by institutions and individuals towards management, and publishing of primary scientific data potentially on a par with recognitions received for scholarly publications. DISCUSSION: This paper reviews the state-of-the-art of primary biodiversity data publishing, and conceptualises a 'Data Publishing Framework' that would help incentivise efforts and investments by institutions and individuals in facilitating free and open access to biodiversity data. It further postulates the institutionalisation of a 'Data Usage Index (DUI)', that would attribute due recognition to multiple players in the data collection/creation, management and publishing cycle. CONCLUSION: We believe that institutionalisation of such a 'Data Publishing Framework' that offers socio-cultural, legal, technical, economic and policy environment conducive for data publishing will facilitate expedited discovery and mobilisation of an exponential increase in quantity of 'fit-for-use' primary biodiversity data, much of which is currently invisible.

Abstract We report data fusion experiments carried out on the four best‐performing retrieval models from TREC 5. Three were conceptually/algorithmically very different from one another; one was algorithmically similar to one of the former. The objective of the test was to observe the performance of the 11 logical data fusion combinations compared to the performance of the four individual models and their intermediate fusions when following the principle of polyrepresentation. This principle is based on cognitive IR perspective (Ingwersen & Järvelin, 2005) and implies that each retrieval model is regarded as a representation of a unique interpretation of information retrieval (IR). It predicts that only fusions of very different, but equally good, IR models may outperform each constituent as well as their intermediate fusions. Two kinds of experiments were carried out. One tested restricted fusions, which entails that only the inner disjoint overlap documents between fused models are ranked. The second set of experiments was based on traditional data fusion methods. The experiments involved the 30 TREC 5 topics that contain more than 44 relevant documents. In all tests, the Borda and CombSUM scoring methods were used. Performance was measured by precision and recall, with document cutoff values (DCVs) at 100 and 15 documents, respectively. Results show that restricted fusions made of two, three, or four cognitively/algorithmically very different retrieval models perform significantly better than do the individual models at DCV100. At DCV15, however, the results of polyrepresentative fusion were less predictable. The traditional fusion method based on polyrepresentation principles demonstrates a clear picture of performance at both DCV levels and verifies the polyrepresentation predictions for data fusion in IR. Data fusion improves retrieval performance over their constituent IR models only if the models all are quite conceptually/algorithmically dissimilar and equally and well performing, in that order of importance.

Abstract In this article, we define webometrics within the framework of informetric studies and bibliometrics, as belonging to library and information science, and as associated with cybermetrics as a generic subfield. We develop a consistent and detailed link typology and terminology and make explicit the distinction among different Web node levels when using the proposed conceptual framework. As a consequence, we propose a novel diagram notation to fully appreciate and investigate link structures between Web nodes in webometric analyses. We warn against taking the analogy between citation analyses and link analyses too far.

Abstract Because of the increasing presence of scientific publications on the Web, combined with the existing difficulties in easily verifying and retrieving these publications, research on techniques and methods for retrieval of scientific Web publications is called for. In this article, we report on the initial steps taken toward the construction of a test collection of scientific Web publications within the subject domain of plant biology. The steps reported are those of data gathering and data analysis aiming at identifying characteristics of scientific Web publications. The data used in this article were generated based on specifically selected domain topics that are searched for in three publicly accessible search engines (Google, AllTheWeb, and AltaVista). A sample of the retrieved hits was analyzed with regard to how various publication attributes correlated with the scientific quality of the content and whether this information could be employed to harvest, filter, and rank Web publications. The attributes analyzed were inlinks, outlinks, bibliographic references, file format, language, search engine overlap, structural position (according to site structure), and the occurrence of various types of metadata. As could be expected, the ranked output differs between the three search engines. Apparently, this is caused by differences in ranking algorithms rather than the databases themselves. In fact, because scientific Web content in this subject domain receives few inlinks, both AltaVista and AllTheWeb retrieved a higher degree of accessible scientific content than Google. Because of the search engine cutoffs of accessible URLs, the feasibility of using search engine output for Web content analysis is also discussed.

No abstract available.

This paper introduces the concepts of the relative relevance (RR) measure and a new performance indicator of the positional strength of the retrieved and ranked documents. The former is seen as a measure of associative performance computed by the application of the Jaccard formula. The latter is named the Ranked Half-Life (RHL) indicator and denotes the degree to which relevant documents are located on the top of a ranked retrieval result. The measures are proposed to be applied in addition to the traditional performance parameters such as precision and/or recall in connection with evaluation of interactive IR systems. The RR measure describes the degree of agreement between the types of relevance applied in evaluation of information retrieval (IR) systems in a non-binary assessment context. It is shown that the measure has potential to bridge the gap between subjective and objective relevance, as it makes it possible to understand and interpret the relation between these two main classes of relevance used in interactive IR experiments. The relevance concepts are defined, and the application of the measures is demonstrated by interrelating three types of relevance assessments: algorithmic; intellectual topical@ and; situational assessments. Further, the paper shows that for a given set of queries at given precision levels the RHL indicator adds to the understanding of comparisons of IR performance.

The aim of the article is to emphasize and illustrate the retrieval dimensions of data collection activity online and their influence on the research evaluation outcome. The attempt is to reinforce the link between online retrieval and bibliometrics. Given that various forms of publication counts and citation analyses provide a valuable and revealing quantitative starting point for more qualitative indications and assessments of Science and Technology (S&T) performance, it is evident that their reliability and objectivity must be undisputed as far as possible. The article discusses the basic problems and limitations inherent in online bibliometric data collection and analyses, and points to possible solutions by means of illustrative case studies and examples. The reason for performing local publication analyses online often arises because of the increased use of external research assessments made by centralized bodies. For small institutions in small countries, like the North European one, such self-analyses may in addition provide valuable and inexpensive insights into novel S&T niches to explore. The major concern is the extent to which online bibliographic and domain dependent databases, as a supplement to the Institute for Scientific Information (ISI) citation files, are suitable for quantitative analysis and mapping of R&D outcome. By merging these two different types of databases into a single cluster, the method of duplicate removal becomes crucial. The article introduces a novel removal procedure by describing and exemplifying the principle of Reversed Duplicate Removal (RDR). RDR enables the analyst to take control of the location of the duplicates and to perform tailored analyses of the overlap of identical documents between files. It is well known that the databases themselves present obstacles directly associated with the process of performing online retrieval of the information necessary for further analysis. Problems encountered are, for instance, poor or inconsistent subject indexing within a single database or among several databases. Name form inconsistencies as to authors, institutions, and journals, the lack or inaccessibility of vital data in the database structures, etc., also present obstacles. On the other hand, comprehensive online bibliometric analyses are in many ways easier, faster, and less expensive to perform locally than those made using the independent CD-ROM versions of the relevant databases. In contrast to the online versions, the CD-ROM systems demonstrate a vital shortage of robust data processing and manipulation facilities. The downloading of records from a variety of CD-ROM files, the cleaning-up process, and the ensuing data processing activities become cumbersome and resource demanding. Regardless of database versioning, the degree of awareness of these retrieval and set isolation factors, such as the relevant search commands, syntax, and the analysis assumptions on the part of the analyst, plays an important role for the quality of the analysis outcome. © 1997 John Wiley & Sons, Inc.

This paper describes the design of the information retrieval facilities of an integrated information system called EUROMATH. EUROMATH is an example of a Knowledge Worker Support System: it has been designed specifically to support mathematicians in their research work. EUROMATH is required to provide uniform retrieval facilities for searching in a user's personal data, in a shared database of structured documents and in public, bibliographic databases. The design of information retrieval facilities that satisfy these and other requirements posed several interesting design issues regarding the integration of various retrieval techniques. As well as a uniform query language, designed to be highly usable by the target user group, the retrieval facilities provide expert intermediary functions, i.e. sophisticated support for the retrieval of bibliographic data. This support is achieved using a model of the user, a model of the user's information need and a set of search strategies based on those used by human intermediaries. The expert intermediary facilities include extensive help facilities, automatic query reformulation and browsing of a variety of sources of query terms.

Focusing on communication, the paper analyses and proposes practical solutions to key problems in online IR, in particular concerned with ill defined and “muddled” information requirements, concept interpretation in searching and text representation.