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Neubert J.,Leibniz Information Center for Economics
Proceedings of the International Conference on Dublin Core and Metadata Applications | Year: 2015

"What's new?" and "What has changed?" are questions users of Knowledge Organization Systems (KOS), such as thesauri or classifications, ask when a new version is published. Much more so, when a thesaurus existing since the 1990s has been completely revised, subject area for subject area. After four intermediately published versions in as many consecutive years, STW Thesaurus for Economics1 has been re-launched recently in version 9.0. In total, 777 descriptors have been added; 1,052 (of about 6,000) have been deprecated and in their vast majority merged into others. More subtle changes include modified preferred labels, or merges and splits of existing concepts. We here describe how these changes were tracked, making use of the published SKOS (Miles & Bechhofer, 2009) files of the versions, loading them into named graphs of a SPARQL endpoint and executing queries on them. An ontology supporting version and delta description and query formulation is introduced. High-level visualizations of aggregated change data and drill-downs to the actual concepts are presented. We finish with an outlook to the skos-history project2, which generalizes and extends the methodology to different knowledge organization systems. © 2015, Dublin Core metadata initiative. All rights reserved.


Morana S.,Karlsruhe Institute of Technology | Schacht S.,Karlsruhe Institute of Technology | Scherp A.,Leibniz Information Center for Economics | Maedche A.,Karlsruhe Institute of Technology
Decision Support Systems | Year: 2017

Guidance design features in information systems are used to help people in decision-making, problem solving, and task execution. Various information systems instantiate guidance design features, which have specifically been researched in the field of decision support systems for decades. However, due to the lack of a common conceptualization, it is difficult to compare the research findings on guidance design features from different literature streams. This article reviews and analyzes the work of the research streams of decisional guidance, explanations, and decision aids conducted in the last 25. years. Building on and grounded by the analyzed literature, we theorize an integrated taxonomy on guidance design features. Applying the taxonomy, we discuss existing empirical results, identify effects of different guidance design features, and propose opportunities for future research. Overall, this article contributes to research and practice. The taxonomy allows researchers to describe their work by using a set of dimensions and characteristics and to systematically compare existing research on guidance design features. From a practice-oriented perspective, we provide an overview on design features to support implementing guidance in various types of information systems. © 2017 Elsevier B.V.


Haustein S.,University of Montréal | Peters I.,Leibniz Information Center for Economics | Bar-Ilan J.,Bar - Ilan University | Priem J.,University of North Carolina at Chapel Hill | And 2 more authors.
Scientometrics | Year: 2013

Altmetrics, indices based on social media platforms and tools, have recently emerged as alternative means of measuring scholarly impact. Such indices assume that scholars in fact populate online social environments, and interact with scholarly products in the social web. We tested this assumption by examining the use and coverage of social media environments amongst a sample of bibliometricians examining both their own use of online platforms and the use of their papers on social reference managers. As expected, coverage varied: 82 % of articles published by sampled bibliometricians were included in Mendeley libraries, while only 28 % were included in CiteULike. Mendeley bookmarking was moderately correlated (.45) with Scopus citation counts. We conducted a survey among the participants of the STI2012 participants. Over half of respondents asserted that social media tools were affecting their professional lives, although uptake of online tools varied widely. 68 % of those surveyed had LinkedIn accounts, while Academia.edu, Mendeley, and ResearchGate each claimed a fifth of respondents. Nearly half of those responding had Twitter accounts, which they used both personally and professionally. Surveyed bibliometricians had mixed opinions on altmetrics' potential; 72 % valued download counts, while a third saw potential in tracking articles' influence in blogs, Wikipedia, reference managers, and social media. Altogether, these findings suggest that some online tools are seeing substantial use by bibliometricians, and that they present a potentially valuable source of impact data. © 2013 Akadémiai Kiadó, Budapest, Hungary.


Latif A.,Leibniz Information Center for Economics | Afzal M.T.,Mohammad Ali Jinnah University | Maurer H.,University of Graz
Journal of Universal Computer Science | Year: 2012

The Linked Open Data project provides a new publishing paradigm for creating machine readable and structured data on the Web. Currently, the significant presence of data sets describing scholarly publications in the Linked Data cloud underpins the importance of Linked Data for the scientific community and for the open access movement. However, these semantically rich datasets need to be exploited and linked with real time applications. In the project we report on this. We have exploited numerous scholarly datasets and have created semantic links to papers in an online journal, particularly Journal of Universal Computer Science (J.UCS). The J. UCS plays an important part in the computer science publishing community and provides a number of innovative features and datasets to its web users. However, the legacy HTML format in which these features are made available makes it difficult for machines to understand and query. Keeping in mind the impressive benefits of the Linked Open Data project, this paper presents an approach to convert J.UCS legacy HTML data from its current form to machine understandable format (RDF). It also interlinks this data with other important Linked Data resources. The approach developed has successfully disambiguated and interlinked J.UCS authors and publications datasets with DBpedia, DBLP, CiteULike and faceted DBLP. Additionally, triplified and interlinked datasets are made available to the scientific and semantic web community for downloading and posing SPARQL queries. This semantically linked dataset can further be used by researchers and semantic agents to identify semantic associations, to build inferencing systems, and to extract useful knowledge. © J.UCS.


Boschen F.,University of Kiel | Scherp A.,Leibniz Information Center for Economics
DocEng 2015 - Proceedings of the 2015 ACM Symposium on Document Engineering | Year: 2015

Existing research on analyzing information graphics assume to have a perfect text detection and extraction available. However, text extraction from information graphics is far from solved. To fill this gap, we propose a novel processing pipeline for multi-oriented text extraction from infographics. The pipeline applies a combination of data mining and computer vision techniques to identify text elements, cluster them into text lines, compute their orientation, and uses a state-of-the-art open source OCR engine to perform the text recognition. We evaluate our method on 121 infographics extracted from an open access corpus of scientific publications. The results show that our approach is effective and significantly outperforms a state-of-the-art baseline. © 2015 ACM.


Abdel-Qader M.,University of Kiel | Scherp A.,Leibniz Information Center for Economics
CEUR Workshop Proceedings | Year: 2016

We analyse the evolution of vocabularies on the Linked Open Data cloud. Based on the recent statistics of the LOD cloud, we have selected the twelve most dominant vocabularies in terms of their use in different pay-level domains. The number of versions we found for these vocabularies range between 2 to 11. While some ontologies exist for more than 10 years (e.g., FOAF) others are only online since a few years (like DCAT). Our analysis shows that many changes occurred on annotation properties. This reects a need for more clarification of the terms, es- pecially at early versions of the vocabularies. The majority of changes in the vocabularies are due to changes in other, imported vocabularies. Thus, there is a co-evolution of different vocabularies. This insight has practical impacts to ontology engineers. They not only need to consider the evolution of the vocabularies they directly use, but also those they import and indirectly depend on.


Nishioka C.,University of Kiel | Scherp A.,Leibniz Information Center for Economics
CEUR Workshop Proceedings | Year: 2016

The Linked Open Data (LOD) cloud is expanding continuously. Entities appear, change, and disappear over time. However, relatively little is known about the dynamics of the entities, i. e., the characteristics of their temporal evolution. In this paper, we employ clustering techniques over the dynamics of entities to determine common temporal patterns. We define an entity as RDF resource together with its attached RDF types and properties. The quality of the clusterings is evaluated using entity features such as the entities' properties, RDF types, and pay-level domain. In addition, we investigate to what extend entities that share a feature value change together over time. As dataset, we use weekly LOD snapshots over a period of more than three years provided by the Dynamic Linked Data Observatory. Insights into the dynamics of entities on the LOD cloud has strong practical implications to any application requiring fresh caches of LOD. The range of applications is from determining crawling strategies for LOD, caching SPARQL queries, to programming against LOD, and recommending vocabularies for reusing LOD vocabularies.


Neubert J.,Leibniz Information Center for Economics
Proceedings of the International Conference on Dublin Core and Metadata Applications | Year: 2012

A large number of library metadata resources have become available as Linked Open Data (LOD) in the last two years. We see, however, not much re-use of this data in library applications. The paper discusses hurdles for a broader adoption of such resources. It suggests building lightweight REST-oriented web service interfaces which fit well in the Web 2.0/Mash-up mindset of the majority of application programmers. Exemplifying this approach in the field of economics, we built and published Web Services for Economics based on a thesaurus, a classification, a personal and a corporate names authority file, all on economics, and interdisciplinary mappings to other terminological resources. Furthermore, we demonstrate how these services are integrated in real-life library applications and how authoring and publishing platforms can be enhanced to make use of them.


Bahls D.,Leibniz Information Center for Economics | Tochtermann K.,Leibniz Information Center for Economics
CEUR Workshop Proceedings | Year: 2013

Statistical research data is the foundation for empirical studies. Researchers in economics or social sciences often obtain such data from external sources through specially designed retrieval interfaces from statistical offices, commercial data providers as well as from data agencies and other archives. With the advancements in data cataloguing and acquisition of long tail research data sets from individual scientists and institutes, the opportunity is there to install central services for a more holistic data search. In view of a rapid increase in amount of data available and by association an emerging retrieval problem, retrieval interfaces must make effective use of provided metadata in order to help Find relevant data sets efficiently. This paper presents a multi-step retrieval interface that aims to support the researchers' natural approach to data search and composition. Starting with an idea of the concepts that are to be compared, users kick off their search with thesauri terms and successively specify requirements according to their priorities until suitable data can be selected easily from a manageable number of matching data sets. The prototype presented in this paper also provides means for convenient data harmonization, which is an essential aspect especially when combining statistical data from different sources. © 2013 for the individual papers by the papers' authors.


Klemenz A.M.,Leibniz Information Center for Economics | Tochtermann K.,Leibniz Information Center for Economics
CEUR Workshop Proceedings | Year: 2013

This position paper as part of a PhD thesis is a contribution to an automatic retrieval of information from the Deep Web. Addressing current limitations of the Deep Web Information Retrieval leads to the prevailing lack of semantics regarding the retrieval process. Focusing this problem from the information providing services perspective, indicates the significant potential of additional semantic annotations provided by websites. Web query interfaces, the interfaces to the majority of available information on the Deep Web, are interpreted as Semantic Deep Web Services (SDWS). The introduction of a SDWS annotation leads to great potential for Information Retrieval services based on the large variety of information available on the Deep Web. © 2013 for the individual papers by the papers' authors.

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