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Purpose: Budgeting data curation tasks in research projects is difficult. In this paper, we investigate the time spent on data curation, more specifically on cleaning and documenting quantitative data for data sharing. We develop recommendations on cost factors in research data management. Design/methodology/approach: We make use of a pilot study conducted at the GESIS Data Archive for the Social Sciences in Germany between December 2016 and September 2017. During this period, data curators at GESIS - Leibniz Institute for the Social Sciences documented their working hours while cleaning and documenting data from ten quantitative survey studies. We analyse recorded times and discuss with the data curators involved in this work to identify and examine important cost factors in data curation, that is aspects that increase hours spent and factors that lead to a reduction of their work. Findings: We identify two major drivers of time spent on data curation: The size of the data and personal information contained in the data. Learning effects can occur when data are similar, that is when they contain same variables. Important interdependencies exist between individual tasks in data curation and in connection with certain data characteristics. Originality/value: The different tasks of data curation, time spent on them and interdependencies between individual steps in curation have so far not been analysed. [ABSTRACT FROM AUTHOR]

The German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of respondents living in private households in Germany. The dataset offers a valuable life course panorama, encompassing living conditions, socioeconomic status, familial connections, personality traits, values, preferences, health, and well-being. To amplify research opportunities further, we have extended the SOEP Innovation Sample (SOEP-IS) by collecting genetic data from 2,598 participants, yielding the first genotyped dataset for Germany based on a representative population sample (SOEP-G). The sample includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 triads, which overlap with the parent-offspring pairs. Leveraging the results from well-powered genome-wide association studies, we created a repository comprising 66 polygenic indices (PGIs) in the SOEP-G sample. We show that the PGIs for height, BMI, and educational attainment capture 22∼24%, 12∼13%, and 9% of the variance in the respective phenotypes. Using the PGIs for height and BMI, we demonstrate that the considerable increase in average height and the decrease in average BMI in more recent birth cohorts cannot be attributed to genetic shifts within the German population or to age effects alone. These findings suggest an important role of improved environmental conditions in driving these changes. Furthermore, we show that higher values in the PGIs for educational attainment and the highest math class are associated with better self-rated health, illustrating complex relationships between genetics, cognition, behavior, socio-economic status, and health. In summary, the SOEP-G data and the PGI repository we created provide a valuable resource for studying individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and the environment. [ABSTRACT FROM AUTHOR]

Copyright of Soziale Welt is the property of Nomos Verlagsgesellschaft mbH & Co. KG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Mitteilungen der DMV is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article provides an overview of the IAB Job Vacancy Survey and its research potential. The IAB Job Vacancy Survey is a quarterly establishment survey covering the (un-)satisfied labor demand in Germany. This survey identifies the entire number of vacancies on the German labor market, including those vacancies that are not reported to the Federal Employment Agency. The main questionnaire obtains information about the number and structure of vacancies, future labor demand, the current economic situation and the expected development of participating establishments. In addition, the questionnaire collects information about the last new hiring and the last case of a failed recruitment process. Finally, the questionnaire enquires about employer attitudes and firms' use of current labor market instruments. The Research Data Centre of the German Federal Employment Agency offers access to the data starting from the survey waves 2000 onwards. [ABSTRACT FROM AUTHOR]

Global societal material stock in buildings and infrastructure have accumulated rapidly within the last decades, along with population growth. Recently, an approach for nation-wide mapping of material stock at 10 m spatial resolution, using freely available and globally consistent Earth Observation (EO) imagery, has been introduced as an alternative to cost-intensive cadastral data or broad-scale but thematically limited nighttime light-based mapping. This study assessed the potential of EO data archives to create spatially explicit time series data of material stock dynamics and their relation to population in Germany, at a spatial resolution of 30 m. We used Landsat imagery with a change-aftereffect-trend analysis to derive yearly masks of land surface change from 1985 onward. Those served as an input to an annual reverse calculation of six material stock types and building volume-based annual gridded population, based on maps for 2018. Material stocks and population in Germany grew by 13% and 4%, respectively, showing highly variable spatial patterns. We found a minimum building stock of ca. 180 t/cap across all municipalities and growth processes characterized by sprawl. A rapid growth of stocks per capita occurred in East Germany after the reunification in 1990, with increased building activity but population decline. Possible over- or underestimations of stock growth cannot be ruled out due to methodological assumptions, requiring further research. [ABSTRACT FROM AUTHOR]

Copyright of Mitteilungen der Berliner Gesellschaft für Anthropologie, Ethnologie und Urgeschichte is the property of Logos Verlag Berlin GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article discusses the role of the RWI, a research institute in collecting multitude of data for scientific community in Germany. It mentions the basic goal of the FDZ Ruhr, a research data center is provide external researchers access to data collected by the RWI within the research project. It also outlines the planned developments towards the availability of research data.

The article examines an employer-employee dataset regarding the impacts of further training in Germany. It states some employment issues included in an employer survey such as the costs and advantages of training, and details on the application of technologies. An employee survey is said to contain the meaning of training measures. Also noted is the role of the Research Data Centre (FDZ) under the German Federal Employment Agency (BA) at the Institute for Employment Research (IAB) in granting access to such information.

Copyright of Schmollers Jahrbuch is the property of Duncker & Humblot GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The collective analysis of long-term field experiments (LTFEs), here defined as agricultural experiments with a minimum duration of 20 years and research in the context of sustainable soil use and yield, can be used for detecting changes in soil properties and yield such as those induced by climate change. However, information about existing LTFEs is scattered, and the research data are not easily accessible. In this study, meta-information on LTFEs in Germany is compiled and their spatial representation is analyzed. The study is conducted within the framework of the BonaRes project, which, inter alia, has established a central access point for LTFE information and research data. A total of 205 LTFEs which fit to the definition above are identified. Of these, 140 LTFEs are ongoing. The land use in 168 LTFEs is arable field crops, in 34 trials grassland, in 2 trials vegetables and in 1 trial pomiculture. Field crop LTFEs are categorized into fertilization (n=158), tillage (n=38) and crop rotation (n=32 ; multiple nominations possible) experiments, while all grassland experiments (n=34) deal with fertilization. The spatial representation is analyzed according to the climatic water balance of the growing season (1 May to 31 October) (CWBg), the Müncheberg Soil Quality Rating (MSQR) and clay content. The results show that, in general, the LTFEs well represent the area shares of both the CWBg and the MSQR classes. Eighty-nine percent of the arable land and 65 % of the grassland in Germany are covered by the three driest CWBg classes, hosting 89 % and 71 % of the arable and grassland LTFEs, respectively. LTFEs cover all six MSQR classes but with a bias towards the high and very high soil quality classes. LTFEs on arable land are present in all clay content classes according to the European Soil Data Centre (ESDAC) but with a bias towards the clay content class 4. Grassland LTFEs show a bias towards the clay content classes 5, 6 and 7, while well representing the other clay content classes, except clay content class 3, where grassland LTFEs are completely missing. The results confirm the very high potential of LTFE data for spatially differentiated analyses and modeling. However, reuse is restricted by the difficult access to LTFE research data. The common database is an important step in overcoming this restriction. [ABSTRACT FROM AUTHOR]

Remote data access, defined as the ability of a researcher to access and evaluate restricted micro data via a secure internet connection from his home desktop computer at any time, has not been implemented by a German Research Data Centre (RDC) so far. Privacy regulations and especially the problem of access control are reasons why German RDCs are not able to offer restricted data via remote data access to the research community. By initiating the "RDC-in-RDC" approach, the Research Data Centre (FDZ) of the German Federal Employment Agency (BA) at the Institute for Employment Research (IAB) in Nuremberg, Germany, aims to bring data access in Germany closer to the ideal perception of remote access. The basic idea is to allow remote data access from designated institutions with comparable standards at locations other than Nuremberg. In a first step, access to BA and IAB data will be granted from four sites in Germany and one site in the US. Moreover, the RDCin- RDC approach represents a change of paradigms in two respects. First, data access will be decentralised and the FDZ literally brings its data closer to the researchers. Second, data of the FDZ will be accessible from abroad so the dissemination of micro data will be no longer restricted to national borders. The RDC-in-RDC approach may therefore be regarded as a first step towards remote access in Germany and may also represent a blue print for an intensified international data sharing [ABSTRACT FROM AUTHOR]

The article provides an overview of data sources from the Economics and Business Data Center (EBDC) Business Expectations Panel and the EBDC Business Investment Panel, which were founded by the University of Munich in Germany and the Ifo Institute for Economic Research. It describes the scope of and access to the EBDC data, the construction of the EBDC data sets, as well as the structure of the EBDC company panels. Some research projects that use the EBDC data sets are also presented.

In Germany as in many other countries there is an abundance of experience with secondary analysis of quantitative data. In particular, the GESIS 'Data Archive and Data Analysis' in Cologne has for more than 50 years supported and promoted this tradition of social science and multidisciplinary research by providing the opportunity to use a wide range of social science data for secondary analysis. A similar picture cannot be drawn for the area of qualitative research in Germany. In spite of the growing relevance of qualitative methods since the 1970s, there is no widespread culture of data sharing in qualitative research nor can one find an institution providing a user-oriented data service for qualitative material on a nationwide scale. In view of this situation the Archive for Life Course Research (ALLF) at the University of Bremen addresses itself to the task of improving the unsatisfactory methodological and data-related conditions through planning for national archival development. As a first step, a nationwide feasibility study on archiving and secondary use of qualitative interview data has been conducted. Drawing on the results of the feasibility study, this contribution reports on the culture of sharing and archiving qualitative research data in Germany, the support for such a service infrastructure, already existing archiving infrastructure, and last but not least, the development planning for the next two years. Due to the ALLF's holdings and the particular value of this kind of data, this overview of the German situation includes a special attention to longitudinal data. [ABSTRACT FROM AUTHOR]

The article focuses on the research data centre (RDC) of the statistical offices of the Länder in Germany. Safe scientific workstations and comprehensive use of microdata in all statistical offices are some of the advantages of RDC. The RDC is funded by the Federal Ministry for Education and Research. It relates the origins and content of the sub-project called Official Firm Data for Germany. It also covers the data sets that will be created during the course of the project.

The article discusses the potential for socio-economic research through longitudinal data from the Research Data Centre of the German Federal Pension Insurance (FDZ-RV). An overview of the longitudinal data of the German Federal Pension Insurance is provided. Also tackled is the development of Scientific Use Files (SUFs) from process-produced data by the FDZ-RV. Processes of statistical matching are said to be capable of enhancing the potential for various analyses regarding the data of the FDZ-RV.

The Sample of Integrated Welfare Benefit Biographies (SIG) is a new administrative longitudinal microdata set representative of recipients of Germany's main welfare programme, the Unemployment Benefit II (UB II, Arbeitslosengeld II). The data set contains detailed longitudinal information on welfare receipt and labour market activities, and hence enables researchers to analyse the dynamics of benefit receipt, income and employment. A distinct feature of the SIG is that it provides information not only for individual benefit recipients but also for family members, including children and partners. This is possible because eligibility for UB II benefits depends on the household structure, and it is means-tested on household income. In addition to socio-demographic and regional information, the SIG contains extensive information on the employment biographies of benefit recipients and their household members from the Integrated Employment Biographies (IEB) of the Institute for Employment Research (IAB). This allows researchers to examine the interaction between labour market participation and benefit receipt. The SIG is available to researchers at the Research Data Centre (FDZ) of the Federal Employment Agency (BA) at the IAB. [ABSTRACT FROM AUTHOR]