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Purpose: In light of a need for more critical education about datafication, this paper aims to develop a framework for critical datafication literacy that is grounded in theoretical and empirical research. The framework draws upon existing critical data literacies, an in-depth analysis of three well-established educational approaches - media literacy, the German "(politische) Bildung" and Freirean "critical pedagogy" - and empirical analyses of online educational resources about datafication. Design/methodology/approach: The study interconnects theoretical analyses with an empirical mixed methods investigation that includes expert interviews with creators of online educational resources about datafication and a qualitative survey with educators interested in teaching about data technologies. Findings: The research identified novel findings on the goals of resource creators and educators, such as a focus on empowering and emancipatory approaches, fostering systemic understanding of datafication and encouraging collective action. Such perspectives are rare in existing critical data literacy conceptualisations but show resemblance to traditional education scholarship. This highlights how much can be learnt from practitioners and from these more established educational approaches. Based on these findings, a framework for critical datafication literacy is suggested that aims for systemic understanding of datafication, encouraging critical thinking and enabling learners to make enlightened choices and take different forms of action. Originality/value: The study is unique in its interconnection of theoretical and empirical research, and it advances previous research by suggesting a grounded framework for critical datafication literacy.

Data and its applications are increasingly ubiquitous in the rapidly digitizing world and consequently, students across different disciplines face increasing demand to develop skills to answer both academia's and businesses' increasing need to collect, manage, evaluate, apply and extract knowledge from data and critically reflect upon the derived insights. On the basis of recent experiences at the University of Ttingen, Germany, we present a new approach to teach the relevant data science skills as an introductory service course at the university or advanced college level. We describe the outline of a complete course that relies on case studies and project work built around contemporary data sets, including openly available online teaching resources.

One question frequently included in surveys asks about respondents' earnings. As this information serves, for example, as a basis for evaluating policy interventions, it must be of high quality. This study aims to advance knowledge about possible measurement errors in earnings data and the potential of data linkage to improve substantive conclusions. We use the German sample of the Programme for the International Assessment of Adult Competencies (PIAAC), a subsample of which could be linked to administrative data from the German Integrated Employment Biographies (IEB). We define measurement error as the difference between administrative and survey data. Our results show differences in the ordinary least squares estimates when the administrative and survey measures of earnings were used as the respective dependent variable, which suggests that measurement error causes biased results. Learning more about the size and type of measurement error can help to correct existing biases and improve the quality of survey data.

The present article aims to show how to model longitudinal change in cohort sequential data applying latent true change models using Mplus' multi-group approach. The underlying modeling ideas are described and explained in this article. As an example, change in internalizing problem behaviors between the age of 8 and 13 years is modeled and predicted by gender. The example data stems from a large German cohort sequential study and comprises 806 children in three birth cohorts (2001, 2000, 1999). Finally, the advantages and disadvantages of this modelling approach are discussed. Annotated syntax is provided online for the models.

This article looks into the processes and outcomes of setting up and maintaining a probability-based longitudinal online survey, which is recruited face-to-face and representative of both the online and the offline population aged 16-75 in Germany. This German Internet Panel studies political and economic attitudes and reform preferences through bimonthly longitudinal online interviews of individuals. The results presented here demonstrate that a carefully designed and implemented online panel can produce high-quality data at lower marginal costs than existing panels that operate solely in a face-to-face mode. Analyses into the representativeness of the online sample showed no major coverage or nonresponse biases. Finally, including offline households in the panel is important as it improves the representation of the older and female segments of the population.

This article introduces the National Educational Panel Study (NEPS). This German longitudinal study produces a vast amount of data for the scientific community, and researchers all around Europe are invited to use the data to address various research questions empirically. Therefore, the authors provide information about the purpose as well as the design of this educational study that has just released data from several starting cohorts, ranging from newborns to adults. As the authors have coordinated the starting cohort of students in lower-secondary school, this target group will be introduced in more detail, with the implementation of NEPS's design being outlined, as well as the tests and survey contents. The analytical potentials are exemplified by the authors' stage-specific research on German-language instruction, the development of orthography competence, and engagement in reading and orthography in lower-secondary school. An overview of different modes of access to the available data completes this research report.

Learning Analytics can provide powerful tools for teachers in order to support them in the iterative process of improving the effectiveness of their courses and to collaterally enhance their students' performance. In this paper, we present the theoretical background, design, implementation, and evaluation details of eLAT, a Learning Analytics Toolkit, which enables teachers to explore and correlate learning object usage, user properties, user behavior, as well as assessment results based on graphical indicators. The primary aim of the development of eLAT is to process large data sets in microseconds with regard to individual data analysis interests of teachers and data privacy issues, in order to help them to self-reflect on their technology-enhanced teaching and learning scenarios and to identify opportunities for interventions and improvements. (Contains 9 figures.)

Purpose: Linking Open Data (LOD) provides a vast amount of well structured semantic information, but many inconsistencies may occur, especially if the data are generated with the help of automated methods. Data cleansing approaches enable detection of inconsistencies and overhauling of affected data sets, but they are difficult to apply automatically. The purpose of this paper is to present WhoKnows?, an online quiz that generates different kinds of questionnaires from DBpedia data sets. Design/methodology/approach: Besides its playfulness, WhoKnows? has been developed for the evaluation of property relevance ranking heuristics on DBpedia data, with the convenient side effect of detecting inconsistencies and doubtful facts. Findings: The original purpose for developing WhoKnows? was to evaluate heuristics to rank LOD properties and thus, obtain a semantic relatedness between entities according to the properties by which they are linked. The presented approach is an efficient method to detect popular properties within a limited amount of triples. Ongoing work continues in the development of sound property ranking heuristics for the purpose of detecting the most relevant characteristics of entities. Originality/value: WhoKnows? uses the approach of "Games with a Purpose" to detect inconsistencies in Linked Data and score properties to rank them for sophisticated semantic search scenarios. (Contains 13 notes, 2 tables and 2 figures.)

Poverty is generally defined as income or expenditure insufficiency, but the economic condition of a household also depends on its real and financial asset holdings. This paper investigates measures of poverty that rely on indicators of household net worth. We review and assess two main approaches followed in the literature: income-net worth measures and asset-poverty. We provide fresh cross-national evidence based on data from the Luxembourg Wealth Study. (Contains 3 figures, 6 tables, and 16 footnotes.)

This paper reports on an empirical case study conducted to investigate the overall conditions and challenges of integrating corpus materials and corpus-based learning activities into English-language classes at a secondary school in Germany. Starting from the observation that in spite of the large amount of research into corpus-based language learning, hands-on work with corpora has remained an exception in secondary schools, the paper starts by outlining a set of pedagogical requirements for corpus integration and the approach which has formed the basis for designing the case study. Then, the findings of the study are reported and discussed. As a result of the methodological challenges identified in the study, the author argues for a move from "data-driven learning" to needs-driven corpora, corpus activities and corpus methodologies.

Describes book ordering procedures at a German pharmaceutical library using the Electronic Data Interchange for Administration, Commerce and Transport (EDIFACT) guidelines developed by the United Nations. Topics include advantages for libraries and for the book trade, changes needed in software, productivity gains, and EDIFACT versus the Internet. (LRW)

Copyright of Public Health Forum 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.)

Background: The surveillance of hospital-acquired infections in Germany is usually conducted via manual chart review; this, however, proves resource intensive and is prone to a certain degree of subjectivity. Documentation based on electronic routine data may present an alternative to manual methods. We compared the data derived via manual chart review to that which was derived from electronic routine data. Methods: Data used for the analyses was obtained from five of the University of Leipzig Medical Center's (ULMC) ICUs. Clinical data was collected according to the Protection against Infection Act (IfSG); documentation thereof was carried out in hospital information systems (HIS) as well as in the ICU-KISS module provided by the National Reference Center for the Surveillance of Nosocomial Infections (NRZ). Algorithmically derived data was generated via an algorithm developed in the EFFECT study; ward-movement data was linked with microbiological test results, generating a data set that allows for evaluation as to whether or not an infection was ICU-acquired. Results: Approximately 75% of MDRO cases and 85% of cases of sepsis/primary bacteremia were classified as ICU-acquired by both manual chart review and EFFECT. Most discrepancies between the manual and algorithmic approaches were due to differentiating definitions regarding the patients' time at risk for acquiring MDRO/bacteremia. Conclusions: The concordance between manual chart review and algorithmically generated data was considerable. This study shows that hospital infection surveillance based on electronically generated routine data may be a worthwhile and sustainable alternative to manual chart review. [ABSTRACT FROM AUTHOR]

Copyright of FinanzRundschau 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.)

On-demand mobility platforms have long struggled with profitability in industrialised nations. To compensate, companies seek out new forms of rationalisation and automation to increase the efficiency of mobility work. Most scholarship on mobility platforms has focussed primarily on the experiences and responses of platform workers to managerial decisions and forms of software-based control; less understood are the managers and technologies themselves. My ethnographic research with logistics management and couriers ('riders') at Fleatz, a German app-based food-delivery company, shows how the effort to increase the efficiency of rider mobilities is underpinned by the central managerial goal of 'breaking even operationally', wherein the cost of providing courier services is offset by the revenue from the orders the couriers fulfil. However, I identify three challenges to increasing rider efficiency: low rider investment in the job, the limitations of rider-management software, and the German political protection of labour and data. Examining platform mobility from both sides of the user interface—from workers' and managers' perspectives—allows us to understand not only the anticipated but also the more hidden limitations of platform rationalisation. [ABSTRACT FROM AUTHOR]

Copyright of Wissenschaftliche Berichte des Instituts für Meteorologie und Klimaforschung des Karlsruher Instituts für Technologie is the property of KIT Scientific Publishing 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 purpose of this explorative study was to examine the use and understanding of key components of data-based decision making by educators in two countries—Germany and the United States. Educators responded to a survey that asked about data use and characteristics related to data-based decision making (DBDM). Results suggest educators in both countries are focused on using data to monitor progress, although less so in Germany. Educators in both countries noted similar understanding of important features (e.g., psychometric properties) of data. Educators in the United States reported they used data for decision making at the classroom level almost twice as often as their counterparts in Germany, while German educators focused on decision making at the student level. These findings will influence future research, including joint studies that could use the best practices of both countries, and professional learning opportunities for educators in Germany and the United States. [ABSTRACT FROM AUTHOR]

Accurate and reliable gridded data sets are important for analyzing extreme weather and climate events. Specifically, these data sets should produce extreme value statistics that are close to reality. Here we use various statistical methods to evaluate the quality of four gridded data products in representing daily precipitation extremes. The data products are the COSMO‐REA6 regional reanalysis, the ERA5 global reanalysis, and the E‐OBS and HYRAS gridded observation‐based data sets. The statistical methods we use offer a thorough insight into the quality of the different data sets by providing temporal and spatial extreme value statistics of daily precipitation. Our results show that all data sets except HYRAS underestimate the magnitude of daily precipitation extremes when compared with weather station data. Moreover, the reanalysis data sets give generally worse extreme value statistics of daily precipitation than the gridded observation‐based data sets. In particular, the reanalysis data sets often fail in reproducing the accurate timing of observed daily precipitation extremes. Plain Language Summary: Gridded data products provide long‐term estimates of climate variables such as temperature and precipitation at regularly spaced grids on the Earth. They are an important source for the research of extreme weather. For example, for investigating the change in frequency and intensity of heavy precipitation over time. To achieve reliable results, we need such data products to be able to accurately represent extreme weather events. To verify if this is the case, we evaluate the quality of several gridded data products in representing heavy daily precipitation events and find that there is room for improvement. Key Points: Most examined gridded data products underestimate the magnitude of observed daily precipitation extremesGridded observation‐based data sets generally perform better than reanalyses in representing daily precipitation extremesReanalyses often fail to capture the timing of observed daily precipitation extremes [ABSTRACT FROM AUTHOR]

Background This report summarizes the results of a voluntary survey designed to assess the current situation of cardiac surgical intensive care medicine in Germany in 2018. Methods A standardized questionnaire concerning detailed information about structural characteristics of cardiac surgical intensive care units (ICUs) was sent to all German departments performing cardiac surgery. Results Response rate was 93% (n = 75/81). Compared with previous surveys since 1998, the median number of intensive care beds for patients after cardiac surgery increased from 15 in 2013 to 16 in 2018. The proportion of cardiac surgical ICUs decreased to 51% with a simultaneous increase of interdisciplinary ICUs. The proportion of cardiac surgeons acting as director of an ICU increased to 43%. The physicians' teams were mostly interdisciplinary (57%). More than half of the directors were board-certified intensivists (62%) with a peak of 100% in ICUs run by cardiac surgeons. Human resources development in the ICU showed similar trends with an increase of physicians and nurses. More than half of all ICUs (61%) and the vast majority of cardiac surgical ICUs (82%) offer an accredited training program for intensive care medicine. Conclusion The results of this survey corroborate once again that intensive care medicine represents a substantial and important part of cardiac surgery. However, efforts are necessary to keep this attitude alive for the future. [ABSTRACT FROM AUTHOR]

Loess proportions in slope deposits have rarely been quantified, due to the lack of quantification methods. In this study, we used laser granulometry to analyze grain‐size distributions in slope deposits of a Buntsandstein landscape in central Germany. The consistent loess contents obtained from two independent models corroborate the validity of the calculated loess proportions and the applicability of the new R package EMMAgeo. Yet, some limitations in transferability need to be considered. [ABSTRACT FROM AUTHOR]

The cybernetic dream of regulatory 'dashboard control' has taken off in the German higher education system. Both government regulators and university managers are engaged in the creation of waves of increasingly fine-grained quantitative data. Yet a wide range of recent case studies of the German higher education sector attest that in spite of this 'datafication' frenzy, the impact of the collected data mass on regulatory and managerial decision-making capacities seems to have remained relatively limited. This article explores why, in spite of the considerable investment in quantitative data infrastructures in the German higher education sector, this did not result in significant overt analytical capacity building. It explores three hypotheses: 1) a legal hypothesis according to which quantification is curbed by legal protections under the Rechtsstaat; 2) a dysfunctionality hypothesis which holds that decision makers reject quantification as a flawed and impracticable pursuit; and 3) an egalitarian federalism hypothesis which argues that Germany's federal states seek to prevent commensurability to avoid comparison and competition. The article finds that, in spite of its inconspicuousness, quantification indeed does inform various central decision-making processes. However, different legal, political, and relational factors prompt decision makers to engage in a hybrid, tempered and, overall, untransparent application of numerical data. [ABSTRACT FROM AUTHOR]

Previous studies show that time series data about the frequency of hits for tourism-related search terms from Google (Google Trends data) is a valuable predictor for short-term tourism demand forecasting in many different tourism regions worldwide. The paper contributes to this literature in three ways. First, it shows that Google Trends data is useful for short-term predictions of monthly tourist arrivals in several German holiday regions. Second, the paper also demonstrates that the Google Trends time series we employ share certain patterns with Google Trends time series used in previous studies, including several studies totally unrelated to the tourism industry. We refer to these artefacts as "spurious patterns" and perform a detailed analysis of their negative impact on forecasting. Last, the paper proposes a method to sanitize Google Trends data and reduce the adverse impact of spurious patterns, thereby paving the way to develop statistically sound tourism demand forecasts. • Google Trends data is a valuable predictor for tourism in Germany. • The data shows "spurious patterns" that are unrelated to tourism. • The spurious patterns have a negative impact on tourism forecasts. • Data modi_cation can reduce the impact of the spurious patterns. • The spurious patterns can be seen in several previously published studies. [ABSTRACT FROM AUTHOR]

The aim of the present study was to investigate the suitability of data obtained from general practices in the UK, France, and Germany for survival analyses in the field of breast cancer (BC). This study included women diagnosed with BC between 2004 and 2008 in 416, 322 and 210 general practices in the UK (n=4,085), France (n=1,198) and Germany (n=2,934), respectively. The outcomes of the study were the mean duration of follow-up in years and the proportion of participants followed for at least 5 years. The mean duration of follow-up was 7.5–9.6 years in the UK, 7.4–8.8 years in France and 6.3–8.5 years in Germany. The proportion of patients followed for at least 5 years was 80–91% in the UK, 68–78% in France, and 55–76% in Germany. The data obtained in general practices in the UK appeared to be more suitable for survival analyses in the field of BC when compared with those obtained in France and Germany. [ABSTRACT FROM AUTHOR]

Rainfall is the most important input for rainfall–runoff models. It is usually measured at specific sites on a daily or sub-daily timescale and requires interpolation for further application. This study aims to evaluate whether a higher temporal and spatial resolution of rainfall can lead to improved model performance. Four different gridded hourly and daily rainfall datasets with a spatial resolution of 1 km × 1 km for the state of Baden-Württemberg in Germany were constructed using a combination of data from a dense network of daily rainfall stations and a less dense network of sub-daily stations. Lumped and spatially distributed HBV models were used to investigate the sensitivity of model performance to the spatial resolution of rainfall. The four different rainfall datasets were used to drive both lumped and distributed HBV models to simulate daily discharges in four catchments. The main findings include that (1) a higher temporal resolution of rainfall improves the model performance if the station density is high; (2) a combination of observed high temporal resolution observations with disaggregated daily rainfall leads to further improvement in the tested models; and (3) for the present research, the increase in spatial resolution improves the performance of the model insubstantially or only marginally in most of the study catchments. [ABSTRACT FROM AUTHOR]

The applicability of a post‐infrared infrared stimulated luminescence (pIRIR290) protocol and two different thermoluminescence (TL) protocols—a single aliquot regeneration (SAR) and a multiple aliquot additive dose (MAAD)—was tested on six polymineral fine‐grain (4–11 μm) samples extracted from the wall remains of a Roman lime kiln and a Roman roof tile. These remains had been excavated close to Bergisch Gladbach, which was at that time part of Germania magna. For the pIRIR290 measurements, no dependence of De on first‐stimulation temperature was detectable, and the standard first stimulation temperature at 50°C was adopted. Fading tests and dose‐recovery tests were made for all samples. Background subtracted glow curves were recorded up to 480°C for TL after a preheat of 220°C for 120 s. A‐values were determined for all TL and pIRIR measurements. The results for all three protocols were fairly consistent, and TL and pIRIR290 protocols are shown to be suitable to estimate reliable equivalent doses for the fired kiln walls. The resulting ages are in agreement with the expected time range—Roman Iron Age—and with independent age control provided by radiocarbon ages of animal bones and charcoal from the firing chamber. Highlights: A Roman lime kiln and surrounding sediments were successfully dated using both thermoluminescence (TL) and post‐infrared infrared stimulated luminescence (pIRIR). [ABSTRACT FROM AUTHOR]

Data is the main resource of the digital economy. Accordingly, personal data constitutes the exchange value for the use of numerous online services such as social media. Many Internet users willingly disclose their data to these services. Oftentimes, there exists a discrepancy between individual privacy preferences and actual behavior. Against this background, this study examines the preferences of the so-called digital natives for privacy. 3,000 students aged between 14 and 21 in Germany were asked about their use of social media and their privacy preferences for these online services. In addition, their willingness to pay for privacy-friendly online services is analyzed. The study shows that while privacy is important to many digital natives, most are not willing to pay for it. [ABSTRACT FROM AUTHOR]

Team personal-life inclusion (Team PLI) refers to socialization with fellow team members in the private domain. While PLI is an expected behavior in the socially oriented Chinese work context, it is generally seen as unfavorable in task-oriented contexts like Germany. We investigate the relative impact of Team PLI on the performance of Chinese and German teams. Based on data from 130 Chinese and 124 German teams, we show that Team PLI has opposing consequences in China and Germany. While it increases German teams’ performance, the reverse relationship was observed for Chinese teams. [ABSTRACT FROM AUTHOR]

Copyright of Journal for Labour Market Research is the property of Springer Nature 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.)

Background: Smoking is suspected to not only be a risk factor for chronic myeloid leukemia but an adverse prognostic factor for the disease as well. The objective of the current study was to investigate the impact of smoking on survival and progression to advanced phases of disease.Methods: Based on the data of the German CML Study IV, the authors analyzed the effect of smoking using a multivariate Cox model with the addition of the European Treatment and Outcome Study (EUTOS) long-term survival score variables of age, spleen size, thrombocytes, and peripheral blasts as well as sex, comorbidities, and type of treatment center.Results: The 8-year survival probability was 87% for a nonsmoking patient and 83% for a patient who smoked. The authors noted a 2.08-times higher risk of death for smokers in comparison with nonsmokers and a 2.11-times higher cause-specific hazard of disease progression. An interaction between smoking and age was found in the model for survival. No significant difference with regard to molecular response was observed.Conclusions: Even when considering differences in socioeconomic status and lifestyle between patients who smoke and nonsmokers, the current analysis demonstrated that smoking also might affect disease biology. The results of the current study indicate that patients with chronic myeloid leukemia, in particular those aged <60 years, should be encouraged to quit smoking. Cancer 2017;123:2467-71. © 2017 American Cancer Society. [ABSTRACT FROM AUTHOR]

As part of the research project Open Data Cloud Services (ODCS), we have been trying to overcome some of the limitations introduced through the heterogeneity of spatial open government data (sOGD). In this paper we describe some of the challenges of sODG and one of the tools we built to spatially organize heterogenous sOGD, to make it easier for users to find data and automatically integrate it into existing data structures and in the future allow for crossdataset spatial analysis. In Europe and beyond the number of sOGD is continuously growing. Derived from government mapping and planning programs, remote sensing and other sources, open spatial government data provides insights into a broad range of topics from geology to weather phenomena, to socio-demographic developments and much more. The data is provided through a variety of government institutions. The distributed generation and provision of spatial data through these different stakeholders has created an extremely heterogenous data space. Heterogenous regarding formats, data structure (time, space, and other attributes), spatial granularity, classification, down to publication cycles and the documentation of changes over time. While national and international working groups are working towards more standardisation, and e.g., in Europe, particularly the INSPIRE (European Commission, 2022) initiative had a positive impact on the standardisation of open spatial data's meta data, as our analysis of all (registered) German open data sets showed, the quality and especially taxonomies still vary strongly between data providers. This heterogeneity presents obstacles for all stakeholders alike from the civil society to researchers to companies trying to build business models on top of open data. The goal is to classify data sets across a variety of spatial hierarchies. An exemplary hierarchy are administrative regions (see figure 1). Classifying a certain dataset to cover a certain state and its granularity to be on a community level, allows users to compare this data set to other data sets of the same granularity for other states. Other exemplary hierarchies in Germany are statistical districts or various grid systems. Beyond inconsistencies within individual hierarchies, calculating relationships between different hierarchies or even non-hierarchical organizational systems, e.g. urban density areas, systems based on natural features, is a challenge, which we are trying to overcome with our work. The ODCS infrastructure is comprised of multiple web services for processing OGD. The pipeline for the spatial classification (see Fig. 2) starts with the 1) aggregation of sOGD's meta data from a variety of sources. The resulting meta data is then 2) homogenized and stored in a central database. Based on the meta data the system then decides if this could potentially be a spatial data set (file format, file name, URL structure, etc.) and then tries to 3) download the actual dataset. The downloaded data is then 4) analysed, if necessary, the analysis and classification process is 5) assisted by a user and the resulting classified data or rather the improved meta data is 6) provisioned to the users of the platform. As described above, the classification should provide improved meta data, to serve users a more precise search and, for future applications, allow for automatic spatial analysis across multiple data sources. To build the classification we primarily rely on spatial hierarchies and relationships between data sets (unconnected, touching, intersecting, containing). To identify those relationships, data sets are analysed threefold: 1) The bounding box of the dataset is calculated and compared to existing bounding boxes in the database. Compared to the next two analysis steps this is fast and works for raster as well as vector datasets. For vector datasets we 2) proceed to generate a "union" from the dataset and then compare the union to other already classified datasets. Exact matches are quite rare (even for datasets from the same provider), therefore, we use buffers on the existing data sets as well as the to be classified data set. As figure 3 illustrates, one and the same border can exist in a variety of geometries. Differences resulting from simplification, generalisation, precision, or actual errors in the data. The differences are in part so big, that we implemented a graphical user interface for human assistance, to manually classify "outliers". If a "good enough" match cannot be found, the next best matches are stored in the database and are then provided to the user to choose from. After the dataset's "union" is analysed, we then 3) split the features up into individual polygons, to again compare those to the already classified polygons in our database. Data sets or rather their polygons that could not be classified are added to the manual classification queue and are then classified by the user. Through this semiautomatic process, the library of polygons quickly grows and increases the automation over time. The system also runs a thematic classification based on meta data and data set attributes, which goes beyond the scope of this paper. Due to the limitations of the abstract, we focused on an overview of the method, rather than the technologies used to perform the analysis. In short: GDAL, OGR2OGR, NodeJS, Python, PostgreSQL + PostGIS. While the above-described use case was developed for Germany's OGD portals, the technique is not limited to German spatial data sets, as all applied methods are not language-depended, but only rely on spatial geometries. Even the metadata homogenization, which is not described in depth in this paper, mostly relies on language-independent methods. [ABSTRACT FROM AUTHOR]

This paper examines the subversive role of statistics paleontology at the end of the 19th and the beginning of the 20th centuries. In particular, I will focus on German paleontology and its relationship with statistics. I argue that in paleontology, the quantitative method was questioned and strongly limited by the first decade of the 20th century because, as its opponents noted, when the fossil record is treated statistically, it was found to generate results openly in conflict with the Darwinian theory of evolution. Essentially, statistics questions the gradual mode of evolution and the role of natural selection. The main objections to statistics were addressed during the meetings at the Kaiserlich- Königliche Geologische Reichsanstalt in Vienna in the 1880s. After having introduced the statistical treatment of the fossil record, I will use the works of Charles Léo Lesquereux (1806-1889), Joachim Barrande (1799-1833), and Henry Shaler Williams (1847-1918) to compare the objections raised in Vienna with how the statistical treatment of the data worked in practice. Furthermore, I will discuss the criticisms of Melchior Neumayr (1845-1890), one of the leading German opponents of statistical paleontology, to show why, and to what extent, statistics were questioned in Vienna. The final part of this paper considers what paleontologists can derive from a statistical notion of data: the necessity of opening a discussion about the completeness and nature of the paleontological data. The Vienna discussion about which method paleontologists should follow offers an interesting case study in order to understand the epistemic tensions within paleontology surrounding Darwin's theory as well as the variety of non-Darwinian alternatives that emerged from the statistical treatment of the fossil record at the end of the 19th century. [ABSTRACT FROM AUTHOR]

The author argues that there are many unanswered questions regarding the legal aspects of automatically generated data, focusing on several developments in Europe involving big data and ownership in data. According to the article, the phrase "big data" is used to describe a variety of data processing services. Other topics include European civil law, as well as the first courts and intellectual property rights to data in Great Britain and Germany.

One major criticism against the use of synthetic data has been that the efforts necessary to generate useful synthetic data are so intense that many statistical agencies cannot afford them. We argue many lessons in this evolving field have been learned in the early years of synthetic data generation, and can be used in the development of new synthetic data products, considerably reducing the required investments. The final goal of the project described in this paper will be to evaluate whether synthetic data algorithms developed in the U.S. to generate a synthetic version of the Longitudinal Business Database (LBD) can easily be transferred to generate a similar data product for other countries. We construct a German data product with information comparable to the LBD - the German Longitudinal Business Database (GLBD) - that is generated from different administrative sources at the Institute for Employment Research, Germany. In a future step, the algorithms developed for the synthesis of the LBD will be applied to the GLBD. Extensive evaluations will illustrate whether the algorithms provide useful synthetic data without further adjustment. The ultimate goal of the project is to provide access to multiple synthetic datasets similar to the SynLBD at Cornell to enable comparative studies between countries. The Synthetic GLBD is a first step towards that goal. [ABSTRACT FROM AUTHOR]

This paper uses comprehensive high-quality panel data from official statistics for exporting enterprises to investigate the micro-structure of the recent export recovery in 2010 in manufacturing industries in Germany after the great recession of 2008/ 2009. Almost all of the increase in exports was due to positive changes of exports in firms that continue to export (i. e. at the so-called intensive margin) while the increase of exports due to export starters (at the so-called extensive margin) was tiny. It is shown that very large firms played a decisive role in shaping the export recovery. These findings are remarkably symmetric to the results from an analysis of the great export collapse of 2008/09. [ABSTRACT FROM AUTHOR]

The papers collected here are the result of an INTERNATIONAL SYMPOSIUM: 'Data · Phenomena · Theories: What's the notion of a scientific phenomenon good for?' held in Heidelberg in September 2008. The event was organized by the research group 'Causality, Cognition, and the Constitution of Scientific Phenomena' in cooperation with Philosophy Department at the University of Heidelberg (Peter McLaughlin and Andreas Kemmerling) and the IWH Heidelberg. The symposium was supported by the 'Emmy-Noether-Programm der Deutschen Forschungsgemeinschaft' and by 'Stiftung Universitat Heidelebrg'. The workshop was held in honor of Daniela Bailer-Jones, who died on 13 November 2006 at the age of 37 (cf. my 2007 'Daniela Bailer-Jones'). Bailer-Jones was an Emmy Noether fellow, and the symposium was arranged and run by those who were working in her research group at the time of her death: Monika Dullstein, Jochen Apel, and Pavel Radchencko. To them goes the credit for the conception, planning, and carrying out of the symposium. [ABSTRACT FROM AUTHOR]

few years ago, a new relative sea-level curve for northwest Germany was constructed for the entire German North Sea coast. It is characterised by several suspected sea-level fluctuations. To test this curve for local effects, it was broken down into five relative sea-level curves representative for five coastal sections. The relative sea-level curves were corrected for tidal effects and also, a rough first correction for compaction was applied. The five curves all differ from the original curve and from each other. Most of the suspected sea-level fluctuations in the original curve cannot be supported and are discussed as data-artefacts or local effects. Around AD 800-1000 all curves show stagnation or drop of sea-level. Thus, this signal is discussed as of over-regional stratigraphic meaning. This study is a first step (1) to show that several curves are needed to demonstrate the Holocene sea-level history of such a big area as the entire German North Sea coast and (2) to establish reliable relative sea-level curves for the German North Sea coast. Further research is necessary to apply detailed corrections especially with respect to compaction-prone data and to improve the individual curves. [ABSTRACT FROM AUTHOR]

While the principle of competition has long been found to be conducive to innovation, community-based innovation contests additionally offer the possibilities of interaction and cooperation among participants. This duality makes innovation contests an interesting field for both academia and practice. However, a surge in practical implementations stands in contrast to a still restricted body of academic knowledge in the field. To close this gap, drawing on a boundary spanning perspective, we examine if and how cooperation in the competitive setting of innovation contests leads to innovativeness. Cooperative orientation of contest participants is explored within a community-based innovation contest run in 2009 at one of the largest universities in Germany. We analyse a complete set of data collected during the contest, data from a follow-up survey among individual participants ( n = 943), as well as video and audio footage from four focus groups. Findings suggest that a very high as well as a very low degree of cooperative orientation result in a high degree of innovativeness, while a medium degree of cooperative orientation results in a low degree of innovativeness. Additionally, this research extends the concept of boundary spanning by identifying two subtypes: proactive and reactive boundary spanning. [ABSTRACT FROM AUTHOR]

A well-established principle of language is that there is a preference for closely related words to be close together in the sentence. This can be expressed as a preference for dependency length minimization (DLM). In this study, we explore quantitatively the degree to which natural languages reflect DLM. We extract the dependencies from natural language text and reorder the words in such a way as to minimize dependency length. Comparing the original text with these optimal linearizations (and also with random linearizations) reveals the degree to which natural language minimizes dependency length. Tests on English data show that English shows a strong effect of DLM, with dependency length much closer to optimal than to random; the optimal English grammar also has many specific features in common with English. In German, too, dependency length is significantly less than random, but the effect is much weaker than in English. We conclude by speculating about some possible reasons for this difference between English and German. [ABSTRACT FROM AUTHOR]

Using data on the ‘career’ paths of one thousand ‘leading scientists’ from 1450 to 1900, what is conventionally called the ‘rise of modern science’ is mapped as a changing geography of scientific practice in urban networks. Four distinctive networks of scientific practice are identified. A primate network centred on Padua and central and northern Italy in the sixteenth century expands across the Alps to become a polycentric network in the seventeenth century, which in turn dissipates into a weak polycentric network in the eighteenth century. The nineteenth century marks a huge change of scale as a primate network centred on Berlin and dominated by German-speaking universities. These geographies are interpreted as core-producing processes in Wallerstein’s modern world-system; the rise of modern scientific practice is central to the development of structures of knowledge that relate to, but do not mirror, material changes in the system. [ABSTRACT FROM AUTHOR]

We estimate a logit scoring model for the prediction of the probability of default by German small and medium-sized enterprises (SMEs) using a unique data set on SME loans in Germany. Our scoring model helps SMEs to gain knowledge about their default risk, which can be used to approximate their risk adequate cost of debt. This knowledge is likely to lead to a detection of hold-up problems that German SMEs might be confronted with in their bank relationships. Furthermore, it allows them to monitor their bank’s pricing behavior and it reduces information asymmetries between lenders and borrowers. Finally, it can influence their future financing decisions toward capital market-based financing. [ABSTRACT FROM AUTHOR]

This paper examines the politicization of gender inequality through a cross-national analysis of attitudes towards inequality between men and women. The data were obtained from national surveys in the United States, Britain, West Germany, Australia and Italy. In all of these countries, attitudes towards gender inequality were found to be associated with the 'left- right' cleavage over economic inequality and redistribution, but they were unrelated to 'new politics' issues. It was also found that attitudes towards gender inequality were more closely integrated into the left-right cleavage in those countries where there was greater awareness of gender issues, and that they had very little net impact on partisanship. Thus high levels of awareness of gender inequality are not associated with the emergence of a new cross-cutting political cleavage. It is concluded that inequality of opportunity between men and women does not constitute part of a new politics agenda, nor does it cross-cut other sources of political interests. It is more plausibly seen as a new element of the well-established left-right cleavage. Consequently, it leaves the structure of political divisions relatively intact. [ABSTRACT FROM AUTHOR]