An increasing demand for bibliometric assessment of individuals has led to a growth of new bibliometric indicators as well as new variants or combinations of established ones. The aim of this review is to contribute with objective facts about the usefulness of bibliometric indicators of the effects of publication activity at the individual level. This paper reviews 108 indicators that can potentially be used to measure performance on individual author-level, and examines the complexity of their calculations in relation to what they are supposed to reflect and ease of end-user application. As such we provide a schematic overview of author-level indicators, where the indicators are broadly categorised into indicators of publication count, indicators that qualify output (on the level of the researcher and journal), indicators of the effect of output (effect as citations, citations normalized to field or the researcher's body of work), indicators that rank the individual's work and indicators of impact over time. Supported by an extensive appendix we present how the indicators are computed, the complexity of the mathematical calculation and demands to data-collection, their advantages and limitations as well as references to surrounding discussion in the bibliometric community. The Appendix supporting this study is available online as supplementary material.

Our results indicate that a specialized search engine can improve the diagnostic quality without compromising the ease of use of the currently widely popular standard web search. The proposed evaluation approach can be valuable for future development and benchmarking. The FindZebra search engine is available at http://www.findzebra.com/.

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We give an overview of the main data of a publication-citation matrix. We show how impact factors are defined, and, in particular, point out the difference between the synchronous and the diachronous impact factor. The advantages and disadvantages of using both as tools in research evaluation are discussed.

Increasingly public bodies and organizations are publishing Open Data for citizens to improve their quality of life and solving public problems. But having Open Data available is not enough. Public engagement is also important for successful Open Data initiatives. There is an increasing demand for strategies to actively involve the public exploiting Open Data, where not only the citizens but also school pupils and young people are able to explore, understand and extract useful information from the data, grasp the meaning of the information, and to visually represent findings. In this research paper, we investigate how we can equip our younger generation with the essential future skills using Open Data as part of their learning activities in public schools. We present the results of a survey among Danish school teachers and pupils. The survey focuses on how we can introduce Open Data visualizations in schools, and what are the possible benefits and challenges for pupils and teachers to use Open Data in their everyday teaching environment. We briefly review Copenhagen city's Open Data and existing open source software suitable for visualization, to study which open source software pupils can easily adapt to visualize Open Data and which data-sets teachers can relate to their teaching themes. Our study shows that introducing Open Data visualizations in schools make everyday teaching interesting and help improving pupils learning skills and that to actively use Open Data visualizations in schools, teachers and pupils need to boost their digital skills.

Private and public institutions are using open and public data to provide better services, which increases the impact of open data on daily life. With the advancement of technology, it becomes also important to equip our younger generation with the essential skills for future challenges. In order to bring up a generation equipped with 21st century skills, open data could facilitate educational processes at school level as an educational resource. Open data could acts as a key resource to enhance the understanding of data through critical thinking and ethical vision among the youth and school pupils. To bring open data into schools, it is important to know the teacher's perspective on open data literacy and its possible impact on pupils. As a research contribution, we answered these questions through a Danish public school teacher's survey where we interviewed 10 Danish public school teachers of grade 5-7th and analyzed their views about the impact of open data on pupils' learning development. After analyzing Copenhagen city's open data, we identified four open data educational themes that could facilitate different subjects, e.g. geography, mathematics, basic science and social science. The survey includes interviews, open discussions, questionnaires and an experiment with the grade 7th pupils, where

In this contribution we investigate the potential influence between assessors' perceived completion of their work task at hand and their actual assessment of usefulness of the retrieved information. The results indicate that the number of useful documents found by assessors does not influence their perception of task completion. Also, with the exception of full text records and across all document types, both measured at rank 10, no statistically significant correlation is observed with respect to retrieval performance influenced by degrees of perceived work task completion or individual types of documents.

Interactive Information Retrieval refers to the branch of Information Retrieval that considers the retrieval process with respect to a wide range of contexts, which may affect the user's information seeking experience. The identification and representation of such contexts has been the object of the principle of Polyrepresentation, a theoretical framework for reasoning about different representations arising from interactive information retrieval in a given context. Although the principle of Polyrepresentation has received attention from many researchers, not much empirical work has been done based on it. One reason may be that it has not yet been formalised mathematically.In this paper we propose an up-to-date and flexible mathematical formalisation of the principle of Polyrepresentation for information needs. Specifically, we apply Subjective Logic to model different representations of information needs as beliefs marked by degrees of uncertainty. We combine such beliefs using different logical operators, and we discuss these combinations with respect to different retrieval scenarios and situations. A formal model is introduced and discussed, with illustrative applications to the modelling of information needs.