Know Center Research

Publikationen

Görögh Edit, Vignoli Michela, Gauch Stephan, Blümel Clemens, Kraker Peter, Hasani-Mavriqi Ilire, Luzi Daniela , Walker Mappet, Toli Eleni, Sifacaki Electra
2017
The growing dissatisfaction with the traditional scholarly communication process and publishing practices as well as increasing usage and acceptance of ICT and Web 2.0 technologies in research have resulted in the proliferation of alternative review, publishing and bibliometric methods. The EU-funded project OpenUP addresses key aspects and challenges of the currently transforming science landscape and aspires to come up with a cohesive framework for the review-disseminate-assess phases of the research life cycle that is fit to support and promote open science. The objective of this paper is to present first results and conclusions of the landscape scan and analysis of alternative peer review, altmetrics and innovative dissemination methods done during the first project year.
Kraker Peter, Enkhbayar Asuraa, Schramm Maxi, Kittel Christopher, Chamberlain Scott, Skaug Mike , Brembs Björn
2017
Görögh Edit, Toli Eleni, Kraker Peter
2017
Kraker Peter, Kittel Christopher, Enkhbayar Asuraa
2016
The goal of Open Knowledge Maps is to create a visual interface to the world’s scientific knowledge. The base for this visual interface consists of so-called knowledge maps, which enable the exploration of existing knowledge and the discovery of new knowledge. Our open source knowledge mapping software applies a mixture of summarization techniques and similarity measures on article metadata, which are iteratively chained together. After processing, the representation is saved in a database for use in a web visualization. In the future, we want to create a space for collective knowledge mapping that brings together individuals and communities involved in exploration and discovery. We want to enable people to guide each other in their discovery by collaboratively annotating and modifying the automatically created maps.
Kraker Peter, Dennerlein Sebastian, Dörler, D, Ferus, A, Gutounig Robert, Heigl, F., Kaier, C., Rieck Katharina, Šimukovic, E., Vignoli Michela
2016
Between April 2015 and June 2016, members of the Open Access Network Aus- tria (OANA) working group “Open Access and Scholarly Communication” met in Vienna to discuss a fundamental reform of the scholarly communication system.By scholarly communication we mean the processes of producing, reviewing, organising, disseminating and preserving scholarly knowledge1. Scholarly communication does not only concern researchers, but also society at large, especially students, educators, policy makers, public administrators, funders, librarians, journalists, practitioners, publishers, public and private organisations, and interested citizens.
Kraker Peter, Peters Isabella, Lex Elisabeth, Gumpenberger Christian , Gorraiz Juan
2016
In this study, we explore the citedness of research data, its distribution overtime and its relation to the availability of a digital object identifier (DOI) in the ThomsonReuters database Data Citation Index (DCI). We investigate if cited research data ‘‘im-pacts’’ the (social) web, reflected by altmetrics scores, and if there is any relationshipbetween the number of citations and the sum of altmetrics scores from various social mediaplatforms. Three tools are used to collect altmetrics scores, namely PlumX, ImpactStory,and Altmetric.com, and the corresponding results are compared. We found that out of thethree altmetrics tools, PlumX has the best coverage. Our experiments revealed thatresearch data remain mostly uncited (about 85 %), although there has been an increase inciting data sets published since 2008. The percentage of the number of cited research datawith a DOI in DCI has decreased in the last years. Only nine repositories are responsible for research data with DOIs and two or more citations. The number of cited research datawith altmetrics ‘‘foot-prints’’ is even lower (4–9 %) but shows a higher coverage ofresearch data from the last decade. In our study, we also found no correlation between thenumber of citations and the total number of altmetrics scores. Yet, certain data types (i.e.survey, aggregate data, and sequence data) are more often cited and also receive higheraltmetrics scores. Additionally, we performed citation and altmetric analyses of allresearch data published between 2011 and 2013 in four different disciplines covered by theDCI. In general, these results correspond very well with the ones obtained for research datacited at least twice and also show low numbers in citations and in altmetrics. Finally, weobserved that there are disciplinary differences in the availability and extent of altmetricsscores.
Kraker Peter, Schlögl Christian, Jack Kris, Lindstaedt Stefanie
2015
Given the enormous amount of scientific knowledge that is produced each and every day, the need for better ways of gaining–and keeping–an overview of research fields is becoming more and more apparent. In a recent paper published in the Journal of Informetrics [1], we analyze the adequacy and applicability of readership statistics recorded in social reference management systems for creating such overviews. First, we investigated the distribution of subject areas in user libraries of educational technology researchers on Mendeley. The results show that around 69% of the publications in an average user library can be attributed to a single subject area. Then, we used co-readership patterns to map the field of educational technology. The resulting knowledge domain visualization, based on the most read publications in this field on Mendeley, reveals 13 topic areas of educational technology research. The visualization is a recent representation of the field: 80% of the publications included were published within ten years of data collection. The characteristics of the readers, however, introduce certain biases to the visualization. Knowledge domain visualizations based on readership statistics are therefore multifaceted and timely, but it is important that the characteristics of the underlying sample are made transparent.
Kraker Peter
2015
In this paper, I present the evaluation of a novel knowledge domain visualization of educational technology. The interactive visualization is based on readership patterns in the online reference management system Mendeley. It comprises of 13 topic areas, spanning psychological, pedagogical, and methodological foundations, learning methods and technologies, and social and technological developments. The visualization was evaluated with (1) a qualitative comparison to knowledge domain visualizations based on citations, and (2) expert interviews. The results show that the co-readership visualization is a recent representation of pedagogical and psychological research in educational technology. Furthermore, the co-readership analysis covers more areas than comparable visualizations based on co-citation patterns. Areas related to computer science, however, are missing from the co-readership visualization and more research is needed to explore the interpretations of size and placement of research areas on the map.
Peters Isabella, Kraker Peter, Lex Elisabeth, Gumpenberger Christian, Gorraiz, Juan
2015
The study explores the citedness of research data, its distribution over time and how it is related to the availability of a DOI (Digital Object Identifier) in Thomson Reuters' DCI (Data Citation Index). We investigate if cited research data "impact" the (social) web, reflected by altmetrics scores, and if there is any relationship between the number of citations and the sum of altmetrics scores from various social media-platforms. Three tools are used to collect and compare altmetrics scores, i.e. PlumX, ImpactStory, and Altmetric.com. In terms of coverage, PlumX is the most helpful altmetrics tool. While research data remain mostly uncited (about 85%), there has been a growing trend in citing data sets published since 2007. Surprisingly, the percentage of the number of cited research data with a DOI in DCI has decreased in the last years. Only nine repositories account for research data with DOIs and two or more citations. The number of cited research data with altmetrics scores is even lower (4 to 9%) but shows a higher coverage of research data from the last decade. However, no correlation between the number of citations and the total number of altmetrics scores is observable. Certain data types (i.e. survey, aggregate data, and sequence data) are more often cited and receive higher altmetrics scores.
Kraker Peter, Schlögl C. , Jack K., Lindstaedt Stefanie
2015
Given the enormous amount of scientific knowledgethat is produced each and every day, the need for better waysof gaining – and keeping – an overview of research fields isbecoming more and more apparent. In a recent paper publishedin the Journal of Informetrics [1], we analyze the adequacy andapplicability of readership statistics recorded in social referencemanagement systems for creating such overviews. First, weinvestigated the distribution of subject areas in user librariesof educational technology researchers on Mendeley. The resultsshow that around 69% of the publications in an average userlibrary can be attributed to a single subject area. Then, we usedco-readership patterns to map the field of educational technology.The resulting knowledge domain visualization, based on the mostread publications in this field on Mendeley, reveals 13 topicareas of educational technology research. The visualization isa recent representation of the field: 80% of the publicationsincluded were published within ten years of data collection. Thecharacteristics of the readers, however, introduce certain biasesto the visualization. Knowledge domain visualizations based onreadership statistics are therefore multifaceted and timely, but itis important that the characteristics of the underlying sample aremade transparent.
Kraker Peter, Enkhbayar Asuraa, Lex Elisabeth
2015
In a scientific publishing environment that is increasingly moving online,identifiers of scholarly work are gaining in importance. In this paper, weanalysed identifier distribution and coverage of articles from the discipline ofquantitative biology using arXiv, Mendeley and CrossRef as data sources.The results show that when retrieving arXiv articles from Mendeley, we wereable to find more papers using the DOI than the arXiv ID. This indicates thatDOI may be a better identifier with respect to findability. We also find thatcoverage of articles on Mendeley decreases in the most recent years, whereasthe coverage of DOIs does not decrease in the same order of magnitude. Thishints at the fact that there is a certain time lag involved, before articles arecovered in crowd-sourced services on the scholarly web.
Vignoli Michela, Kraker Peter, Sevault A.
2015
Science 2.0 is the current trend towards using Web 2.0 tools in research and practising a more open science. We are currently at the beginning of a transition phase in which traditional structures, processes, value systems, and means of science communication are being put to the proof. New strategies and models under the label of “open” are being explored and partly implemented. This situation implies a number of insecurities for scientists as well as for policy makers and demands a rethinking and overcoming of some habits and conventions persisting since an era before the internet. This paper lists current barriers to practising Open Science from the point of view of researchers and reflects which measures could help overcoming them. The central question is which initiatives should be taken on institutional or political level and which ones on level of the community or the individual scientist to support the transition to Science 2.0.
Buschmann Katrin, Kasberger Stefan, Mayer Katja, Reckling Falk, Rieck Katharina, Vignoli Michela, Kraker Peter
2015
Insbesondere in den letzten zwei Jahren hat Österreichim Bereich Open Science, vor allem was Open Accessund Open Data betrifft, nennenswerte Fortschritte gemacht.Die Gründung des Open Access Networks Austria(OANA) und das Anfang 2014 gestartete Projekt e-InfrastructuresAustria können als wichtige Grundsteine fürden Ausbau einer österreichischen Open-Science-Landschaftgesehen werden. Auch das österreichische Kapitelder Open Knowledge Foundation leistet in den BereichenOpen Science Praxis- und Bewusstseinsbildung grundlegendeArbeit. Unter anderem bilden diese Initiativendie Grundlage für den Aufbau einer nationalen Open-Access-Strategie sowie einer ganz Österreich abdeckendenInfrastruktur für Open Access und Open (Research) Data.Dieser Beitrag gibt einen Überblick über diese und ähnlichenationale sowie lokale Open-Science-Projekte und-Initiativen und einen Ausblick in die mögliche Zukunftvon Open Science in Österreich.
Kraker Peter, Lex Elisabeth, Gorraiz Juan, Gumpenberger Christian, Peters Isabella
2015
Kraker Peter, Lindstaedt Stefanie , Schlögl C., Jack K.
2015
In this paper, we analyze the adequacy and applicability of readership statistics recorded in social reference management systems for creating knowledge domain visualizations. First, we investigate the distribution of subject areas in user libraries of educational technology researchers on Mendeley. The results show that around 69% of the publications in an average user library can be attributed to a single subject area. Then, we use co-readership patterns to map the field of educational technology. The resulting visualization prototype, based on the most read publications in this field on Mendeley, reveals 13 topic areas of educational technology research. The visualization is a recent representation of the field: 80% of the publications included were published within ten years of data collection. The characteristics of the readers, however, introduce certain biases to the visualization. Knowledge domain visualizations based on readership statistics are therefore multifaceted and timely, but it is important that the characteristics of the underlying sample are made transparent.
Lex Elisabeth, Kraker Peter, Dennerlein Sebastian
2014
Today’s data driven world requires interdisciplinary, teamoriented approaches: experts from different disciplines are needed to collaboratively solve complex real-world problems. Interdisciplinary teams face a set of challenges that are not necessarily encountered by unidisciplinary teams, such as organisational culture, mental and financial barriers. We share our experiences with interdisciplinary teamwork based on a real-world example. We found that models of interdisciplinary teamwork from Social Sciences and Web Science can guide interdisciplinary teamwork in the domain of pharmaceutical knowledge management. Additionally, we identified potential extensions of the models’ components as well as novel influencing factors such the willingness to explicate and share domain knowledge.
Trattner Christoph, Smadi Mohammad, Theiler Dieter, Dennerlein Sebastian, Kowald Dominik, Rella Matthias, Kraker Peter, Barreto da Rosa Isaías, Tomberg Vladimir, Kröll Mark, Treasure-Jones Tamsin, Kerr Micky, Lindstaedt Stefanie , Ley Tobias
2013
Kraker Peter, Trattner Christoph, Jack Kris, Lindstaedt Stefanie , Schlgl Christian
2013
At the beginning of a scientific study, it is usually quite hardto get an overview of a research field. We aim to addressthis problem of classic literature search using web data. Inthis extended abstract, we present work-in-progress on aninteractive visualization of research fields based on readershipstatistics from the social reference management systemMendeley. To that end, we use library co-occurrences as ameasure of subject similarity. In a first evaluation, we findthat the visualization covers current research areas withineducational technology but presents a view that is biasedby the characteristics of readers. With our presentation, wehope to elicit feedback from the Websci’13 audience on (1)the usefulness of the prototype, and (2) how to overcomethe aforementioned biases using collaborative constructiontechniques.
Dennerlein Sebastian, Gutounig Robert, Kraker Peter, Kaiser Rene_DB, Rauter Romana , Ausserhofer Julian
2013
Barcamps are informal conferences whose content is not de-fined in advance, often referred to as ad-hoc conferences orun-conferences. Therefore, the outcomes of a barcamp arelargely unknown before the event. This raises the question ofthe participants’ motivations to attend and contribute. Toanswer this question, we conducted an exploratory empiricalstudy at Barcamp Graz 2012. We applied a mixed-methodapproach: first we used a socio-demographic questionnaire(n=99) which allowed us to characterize the ’typical barcamper’.Second, we conducted qualitative interviews (n=10) toget a deeper understanding of the participants’ motivationsto attend, expectations, and the use of social media in thatcontext. We identified three concepts, which could be deductedfrom the interviews: people, format and topics. Wefound that the motivation to attend and even a commonidentity is quite strongly based on these three factors. Furthermore,the results indicate that participants share a set ofactivities and methods by following the barcamp’s inherentrules and make extensive use of social media.
Kraker Peter, Dennerlein Sebastian
2013
In this position paper, we argue that the different disciplinesin Web Science do not work together in an interdisciplinaryway. We attribute this to a fundamental difference in approachingresearch between social scientists and computerscientists, which we call the patterns vs. model problem.We reason that interdisciplinary teamwork is needed toovercome the patterns vs. model problem. We then discusstwo theoretical strains in social science which we see asrelevant in the context of interdisciplinary teamwork. Finally,we sketch a model of interdisciplinary teamwork in WebScience based on the interplay of collaboration and cooperation.
Lindstaedt Stefanie , Kraker Peter, Wild Fridolin, Ullmann Thomas, Duval Erik, Parra Gonzalo
2011
This deliverable reports on first usage experiences and evaluations of the STELLAR Science 2.0 Infrastructure. Usage experiences were available predominantly for the "mature" part of the infrastructure provided by standard Web 2.0 tools adapted to STELLAR needs. Evaluations are provided for newly developed tools. We first provide an overview of the whole STELLAR Science 2.0 Infrastructure and the relationships between the building blocks. While the individual building blocks already benefit researchers, the integration between them is the key for a positive usage experience. The publication meta data ecosystem for example provides researchers with an easy to retrieve set of TEL related data. Tools like the ScienceTable, Muse, the STELLAR latest publication widget, and the STELLAR BuRST search show already several scenarios of how to make use of this infrastructure. Especially a strong focus on anlytical tools based on publication and social media data seem useful. In order to highlight the relevance of the infrastructure to the individual capacitiy building activties within STELLAR, the usage experiences of individual building blocks are then reported with respect to Researcher Capacity (e.g. Deliverable Wikis, More! application), Doctoral Academy Capacity (e.g. DoCoP), Community Level Capacity (e.g TELeurope), and Leadership Capacity (e.g. Meeting of Minds, Podcast Series). Here we draw from 11 scientific papers published. The reader will find an overview of all these papers in the Appendix. Based on the usage experiences and evaluations we have identified a number of ideas which might be worth considering for future developments. For example, the experiences gained with the Deliverable Wikis show how the modification of the standard Wiki history can provide useful analytical insights into the collaboration of living deliverables and can return the focus on authorship (which is intentionally masked in Wikis, because of their strong notion on the product and not on authors). We conclude with main findings and an outlook on the development plan and evaluation plan which are currently being developed and which will influence D6.6. Particularly, we close with the notion of a Personal Research Environment (PRE) which draws from the concept of Personal Learning Environments (PLE).
Kraker Peter, Wagner Claudia, Jeanquartier Fleur, Lindstaedt Stefanie
2011
This paper presents an adaptable system for detecting trends based on the micro-blogging service Twitter, and sets out to explore to what extent such a tool can support researchers. Twitter has high uptake in the scientific community, but there is a need for a means of extracting the most important topics from a Twitter stream. There are too many tweets to read them all, and there is no organized way of keeping up with the backlog. Following the cues of visual analytics, we use visualizations to show both the temporal evolution of topics, and the relations between different topics. The Twitter Trend Detection was evaluated in the domain of Technology Enhanced Learning (TEL). The evaluation results indicate that our prototype supports trend detection but reveals the need for refined preprocessing, and further zooming and filtering facilities.
Stern Hermann, Kaiser Rene_DB, Hofmair P., Lindstaedt Stefanie , Scheir Peter, Kraker Peter
2010
One of the success factors of Work Integrated Learning (WIL) is to provide theappropriate content to the users, both suitable for the topics they are currently working on, andtheir experience level in these topics. Our main contributions in this paper are (i) overcomingthe problem of sparse content annotation by using a network based recommendation approachcalled Associative Network, which exploits the user context as input; (ii) using snippets for notonly highlighting relevant parts of documents, but also serving as a basic concept enabling theWIL system to handle text-based and audiovisual content the same way; and (iii) using the WebTool for Ontology Evaluation (WTE) toolkit for finding the best default semantic similaritymeasure of the Associative Network for new domains. The approach presented is employed inthe software platform APOSDLE, which is designed to enable knowledge workers to learn atwork.
Lindstaedt Stefanie , Kraker Peter, Höfler Patrick, Fessl Angela
2010
In this paper we present an ecosystem for the lightweight exchangeof publication metadata based on the principles of Web 2.0. At the heart of thisecosystem, semantically enriched RSS feeds are used for dissemination. Thesefeeds are complemented by services for creation and aggregation, as well aswidgets for retrieval and visualization of publication metadata. In twoscenarios, we show how these publication feeds can benefit institutions,researchers, and the TEL community. We then present the formats, services,and widgets developed for the bootstrapping of the ecosystem. We concludewith an outline of the integration of publication feeds with the STELLARNetwork of Excellence1 and an outlook on future developments.