128 research outputs found

    Strategien bei der Veröffentlichung von Forschungsdaten

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    Forschungsdaten liegen in AbhÀngigkeit der Disziplinen in vielfÀltigen Formen und Formaten vor. Sie sind in allen Disziplinen Teil des wissenschaftlichen Erkenntnisprozesses. Als digitales Informationsobjekt sind sie komplex und bislang wenig untersucht. Mit den Möglichkeiten neuer Informationstechnologien werden in den letzten Jahren neue Wege in der Publikation von Forschungsdaten beschritten. Mit Blick auf die Naturwissenschaften werden im Folgenden drei Publikationsmodelle beschrieben: Die Veröffentlichung von Forschungsdaten als eigenstÀndiges Objekt in einem Forschungsdatenrepositorium, die Veröffentlichung von Forschungsdaten mit textueller Dokumentation und die Veröffentlichung von Forschungsdaten als Anreicherung einer interpretativen Text-Publikation.

    Strategien bei der Veröffentlichung von Forschungsdaten

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    Forschungsdaten liegen in AbhÀngigkeit der Disziplinen in vielfÀltigen Formen und Formaten vor. Sie sind in allen Disziplinen Teil des wissenschaftlichen Erkenntnisprozesses. Als digitales Informationsobjekt sind sie komplex und bislang wenig untersucht. Mit den Möglichkeiten neuer Informationstechnologien werden in den letzten Jahren neue Wege in der Publikation von Forschungsdaten beschritten. Mit Blick auf die Naturwissenschaften werden im Folgenden drei Publikationsmodelle beschrieben: Die Veröffentlichung von Forschungsdaten als eigenstÀndiges Objekt in einem Forschungsdatenrepositorium, die Veröffentlichung von Forschungsdaten mit textueller Dokumentation und die Veröffentlichung von Forschungsdaten als Anreicherung einer interpretativen Text-Publikation

    Drivers and barriers in digital scholarly communication

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    Zwei Innovationen innerhalb von Open Science werden in dieser Dissertation untersucht: Open Access und der Umgang mit Forschungsdaten. Die Ergebnisse zeigen ein positives Meinungsbild gegenĂŒber beiden Innovationen, was sich allerdings nicht in einer ĂŒbergreifenden Umsetzung in der Wissenschaft niederschlĂ€gt. Die disziplinĂ€ren Unterschiede sind markant. Es lassen sich aber ĂŒbergeordnete Ebenen herausarbeiten: Soziologische, technische & infrastrukturelle, sowie strategische & monetĂ€re Aspekte gehören hierzu, wobei starke Interdependenzen zu verorten sind. Traditionell werden QualitĂ€t und Prestige von veröffentlichten wissenschaftlichen Ergebnissen als Maßgabe fĂŒr die Reputation eines Wissenschaftlers angesehen, was klar in den Resultaten dieser Arbeit reflektiert ist. Sie prĂ€ferieren die Nutzung von Publikationsorganen und ArbeitsablĂ€ufen, die in der Fachgemeinschaft etabliert sind. Daraus folgt ein zögerlicher Umgang mit Innovationen, z.B. dem offenem Zugang zu Forschungsdaten, wo es nur wenige etablierte AblĂ€ufe gibt. In der Diskussion dieser Arbeit wird die Notwendigkeit einer Verbindung zu heutigen Anreizsystemen und damit den Evaluierungssystemen in der Wissenschaft herausgestellt. Neue Strategien diesbezĂŒglich sind im Aufbau, z.B. mit “zĂ€hlbaren” Publikationen und Zitationen fĂŒr Forschungsdaten. Die Kernthemen wurden in der Fallstudie der Hochenergiephysik genauer untersucht. Eine digitale Bibliothek erlaubte dort die praktische Implementierung von Open Science Werkzeugen. Die Ergebnisse unterstreichen das Potential: mit gezielten Diensten und Anreizen können Wissenschaftler fĂŒr Open Science gewonnen werden; in diesem Fall zur Teilnahme in einem Crowdsourcingprojekt der digitalen Bibliothek und zur Umsetzung von „data sharing“. Dem Informationsmanagement kommt dabei eine neue Rolle zu, insbesondere bei einer engen Betreuung von Wissenschaftlern im digitalen Forschungsumfeld. Das kann parallel fĂŒr die Serviceentwicklung und –begleitung genutzt werden.Two major Open Science innovations, Open Access and research data sharing, have been studied in detail in this thesis. A large-scale survey and personal interviews are used to gain detailed insights from a range of disciplines. In addition, a case study in the High Energy Physics (HEP) community was used to study the results in practice. The results show that a rather positive attitude towards both, Open Access and research data sharing is not reflected in the researchers’ practices. Disciplinary differences prevail and relate to the different publishing cultures and research workflows. The results indicate that quality and prestige of research output are perceived as very important in determining a researcher’s reputation. Researchers prefer community-approved publication outlets. They hesitate to explore new innovations, such as data sharing, for which only few established workflows exist in digital scholarly communication. Interviewees highlight the significance of a (missing) link between such approaches on the one hand and the current incentive system and the research assessment schemes on the other. The results indicate that barriers can be overcome. In the case study, a strong collaboration with the community facilitated enhanced feedback loops to develop tailored and targeted services for Open Science. Researchers in the case study were successfully engaged in new innovative workflows: a crowdsourcing tool and data sharing in a digital library. The results highlight that opportunities of Open Science are not yet explored widely. But with targeted support, it is possible to build on best practices and develop strategies that engage communities in new innovations. The results furthermore demand new strategies to establish links from Open Science services to the academic incentive system. It is needed to revisit the current research assessment scheme in regard to potential support mechanisms for Open Science

    Query Expansion for Survey Question Retrieval in the Social Sciences

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    In recent years, the importance of research data and the need to archive and to share it in the scientific community have increased enormously. This introduces a whole new set of challenges for digital libraries. In the social sciences typical research data sets consist of surveys and questionnaires. In this paper we focus on the use case of social science survey question reuse and on mechanisms to support users in the query formulation for data sets. We describe and evaluate thesaurus- and co-occurrence-based approaches for query expansion to improve retrieval quality in digital libraries and research data archives. The challenge here is to translate the information need and the underlying sociological phenomena into proper queries. As we can show retrieval quality can be improved by adding related terms to the queries. In a direct comparison automatically expanded queries using extracted co-occurring terms can provide better results than queries manually reformulated by a domain expert and better results than a keyword-based BM25 baseline.Comment: to appear in Proceedings of 19th International Conference on Theory and Practice of Digital Libraries 2015 (TPDL 2015

    Assigning Creative Commons Licenses to Research Metadata: Issues and Cases

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    This paper discusses the problem of lack of clear licensing and transparency of usage terms and conditions for research metadata. Making research data connected, discoverable and reusable are the key enablers of the new data revolution in research. We discuss how the lack of transparency hinders discovery of research data and make it disconnected from the publication and other trusted research outcomes. In addition, we discuss the application of Creative Commons licenses for research metadata, and provide some examples of the applicability of this approach to internationally known data infrastructures.Comment: 9 pages. Submitted to the 29th International Conference on Legal Knowledge and Information Systems (JURIX 2016), Nice (France) 14-16 December 201

    Open Data and Data Analysis Preservation Services for LHC Experiments

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    In this paper we present newly launched services for open data and for long-term preservation and reuse of high-energy-physics data analyses based on the digital library software Invenio. We track the ”data continuum” practices through several progressive data analysis phases up to the final publication. The aim is to capture for subsequent generations all digital assets and associated knowledge inherent in the data analysis process, and to make a subset available rapidly to the public. The ultimate goal of the analysis preservation platform is to capture enough information about the processing steps in order to facilitate reproduction of an analysis even many years after its initial publication, permitting to extend the impact of preserved analyses through future revalidation and recasting services. A related ”open data” service was launched for the benefit of the general public.Peer Reviewe

    Connecting Data Publication to the Research Workflow: A Preliminary Analysis

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    The data curation community has long encouraged researchers to document collected research data during active stages of the research workflow, to provide robust metadata earlier, and support research data publication and preservation. Data documentation with robust metadata is one of a number of steps in effective data publication. Data publication is the process of making digital research objects ‘FAIR’, i.e. findable, accessible, interoperable, and reusable; attributes increasingly expected by research communities, funders and society. Research data publishing workflows are the means to that end. Currently, however, much published research data remains inconsistently and inadequately documented by researchers. Documentation of data closer in time to data collection would help mitigate the high cost that repositories associate with the ingest process. More effective data publication and sharing should in principle result from early interactions between researchers and their selected data repository. This paper describes a short study undertaken by members of the Research Data Alliance (RDA) and World Data System (WDS) working group on Publishing Data Workflows. We present a collection of recent examples of data publication workflows that connect data repositories and publishing platforms with research activity ‘upstream’ of the ingest process. We re-articulate previous recommendations of the working group, to account for the varied upstream service components and platforms that support the flow of contextual and provenance information downstream. These workflows should be open and loosely coupled to support interoperability, including with preservation and publication environments. Our recommendations aim to stimulate further work on researchers’ views of data publishing and the extent to which available services and infrastructure facilitate the publication of FAIR data. We also aim to stimulate further dialogue about, and definition of, the roles and responsibilities of research data services and platform providers for the ‘FAIRness’ of research data publication workflows themselves
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