Search results

Big Data ist in aller Munde. Aber was bedeutet Big Data für die Demokratie? Ziel des vorliegenden Bandes ist es, den Bezug von Big Data zur demokratischen Willensbildung herzustellen, einen Bezug, der in der Diskussion um diese neuen Datenverarbeitungsmethoden meist fehlt oder viel zu kurz kommt.Wie verändert Big Data das Verhältnis von Privatheit und Öffentlichkeit? Welche Auswirkung haben diese Veränderungen wiederum auf den politischen Diskurs, auf Wahlkämpfe und die demokratische Kultur insgesamt? Überwiegen die Vorteile oder die Nachteile? Wie können Privatheit und Öffentlichkeit neu justiert und ausbalanciert werden, um eine freie Willensbildung auch im Zeitalter von Big Data zu gewährleisten? Wissenschaftler aus Informatik, Rechtswissenschaft, Ethik, Soziologie und Psychologie bearbeiten vorliegend diese Fragen und eröffnen damit die interdisziplinäre Diskussion, über Phänomene der modernen Datenverarbeitung, die bereits im Begriff sind, etablierte Vorstellungen von parlamentarischer Demokratie fundamental in Frage zu stellen. Mit Beiträgen von: Prof. Dr. Rüdiger Grimm, Dr. Jessica Heesen, Dr. Tobias Matzner, Dr. Carsten Ochs, Dr. Philipp Richter, Ass. Iur. Maxi Nebel, RA Stephan Sädtler, FAIT-Recht, Hervais Simo Fhom, Dipl.-Psych. Tobias Dienlin

Data sharing is increasingly perceived to be beneficial to knowledge production, and is therefore increasingly required by federal funding agencies, private funders, and journals. As qualitative researchers are faced with new expectations to share their data, data repositories and academic libraries are working to address the specific challenges of qualitative research data. This article describes how data repositories and academic libraries can partner with researchers to support three challenges associated with qualitative data sharing: (1) obtaining informed consent from participants for data sharing and scholarly reuse, (2) ensuring that qualitative data are legally and ethically shared, and (3) sharing data that cannot be deidentified. This article also describes three continuing challenges of qualitative data sharing that data repositories and academic libraries cannot specifically address—research using qualitative big data, copyright concerns, and risk of decontextualization. While data repositories and academic libraries cannot provide easy solutions to these three continuing challenges, they can partner with researchers and connect them with other relevant specialists to examine these challenges. Ultimately, this article suggests that data repositories and academic libraries can help researchers address some of the challenges associated with ethical and lawful qualitative data sharing.

Abstract
The paper presents results of spatial analysis of huge volume of AIS data with the goal to detect predefined maritime anomalies. The maritime anomalies analysed have been grouped into: traffic analysis, static anomalies, and loitering detection. The analysis was carried out on data describing movement of tankers worldwide in 2015, using sophisticated algorithms and technology capable of handling big data in a fast and efficient manner. The research was conducted as a follow-up of the EDA-funded SIMMO project, which resulted in a maritime surveillance system based on AIS messages enriched with data acquired from open Internet sources.

The Indian government suspended research in April 2010 on the feasibility and safety of human papillomavirus (HPV) vaccine in two Indian states (Andhra Pradesh and Gujarat) amid public concerns about its safety. This paper describes cervical cancer and cancer surveillance in India and reviews the epidemiological claims made by the Programme for Appropriate Technology in Health (PATH) in support of the vaccine in these two states. National cancer data published by the Indian National Cancer Registry Programme of state registry returns and the International Agency for Research on Cancer cover around seven percent of the population with underrepresentation of rural, northern, eastern and north-eastern areas. There is no cancer registry in the state of Andhra Pradesh and PATH does not cite data from the Gujarat cancer registries. Age-adjusted cervical cancer mortality and incidence rates vary widely across and within states. National trends in age standardized cervical cancer incidence fell from 42.3 to 22.3 per 100,000 between 1982/1983 and 2004/2005 respectively. Incidence studies report low incidence and mortality rates in Gujarat and Andhra Pradesh. Although HPV prevalence is higher in cancer patients (93.3%) than healthy patients (7.0%) and HPV types 16 and 18 are most prevalent in cancer patients, population prevelance data are poor and studies highly variable in their findings. Current data on HPV type and cervical cancer incidence do not support PATH's claim that India has a large burden of cervical cancer or its decision to roll out the vaccine programme. In the absence of comprehensive cancer surveillance, World Health Organization criteria with respect to monitoring effectiveness of the vaccine and knowledge of disease trends cannot be fulfilled.