Suchergebnisse

Ziel dieser Studie war es, die Einstellung gegenüber Datenaustausch- und Datenerhebungsorganisationen vor und nach der Einführung der Datenschutz-Grundverordnung (DSGVO) der EU von Personen in Deutschland zu messen. Die Daten stammen aus einer dreistufigen Split-Panel-Webbefragung unter Personen ab 18 Jahren in Deutschland, die aus einem deutschen, Nicht-Wahrscheinlichkeits-Online-Panel rekrutiert wurden. Im April 2018 (vor dem Inkrafttreten der DSGVO) füllten 2.095 Teilnehmer den Welle 1-Fragebogen über Gerätebesitz, Social Media-Nutzung, Vertrauen in verschiedene Datenerfassungsorganisationen, Bereitschaft zum Datenaustausch, allgemeines Vertrauen, Bewusstsein und Wissen über die DSGVO sowie Datenschutzbelange aus. Im Juli und Oktober 2018 (nach Inkrafttreten der DSGVO) wurden die Befragten aus den früheren Wellen zu einer zweiten und dritten Webumfrage eingeladen, die die meisten Fragen der ersten Welle wiederholte. Zusätzlich zu den Teilnehmern aus den früheren Wellen wurden auch neue Teilnehmer zu den Wellen 2 und 3 eingeladen. Insgesamt 2.046 (Welle 2) und 2.117 (Welle 3) Teilnehmer füllten den Fragebogen der folgenden Wellen aus. 1.269 Teilnehmer nahmen an allen drei Wellen teil.

Themen:

Welle 1

Besitz von Smartphone, Handy, PC, Tablet und/oder E-Book-Reader; Social-Media-Nutzung: Account mit Benutzernahme und Passwort bei ausgewählten Anbietern (Google, Facebook, Twitter, LinkedIn, Xing); Vertrauen in Institutionen (Google, Facebook, Bundesamt für Statistik, Universitätsforscher) im Hinblick auf den Schutz persönlicher Daten und Begründung diese Einschätzung; Wahrscheinlichkeitsskala im Hinblick auf den Schutz persönlicher Daten bei den zuvor genannten Institutionen und Gründe für diese Einschätzung; Einverständnis mit dem Zuspielen persönlicher Daten der Sozialversicherungsträger zu den Umfragedaten; allgemeines Personenvertrauen; Bekanntheit der Datenschutz-Grundverordnung (DSGVO) der EU; Wissenstest: Ziele der DSGVO (offen); Gefühl verletzter Privatsphäre durch folgende Institutionen: Google, Facebook, Staatliche Behörden, Universitätsforscher; allgemeine Datenschutzbedenken.

Welle 2:

Besitz von Smartphone, Handy, PC, Tablet und/oder E-Book-Reader; Social-Media-Nutzung: Account mit Benutzernahme und Passwort bei ausgewählten Anbietern (Google, Facebook, Twitter, LinkedIn, Xing); Vertrauen in Institutionen (Google, Facebook, Bundesamt für Statistik, Universitätsforscher) im Hinblick auf den Schutz persönlicher Daten; allgemeines Personenvertrauen; Bekanntheit der Datenschutz-Grundverordnung (DSGVO) der EU; Wissenstest: Ziele der DSGVO (offen); Einverständnis mit dem Speichern verschiedener persönlicher Daten durch Facebook bzw. Google (Name, E-Mail Adresse, Wohnadresse, Geburtsdatum, Telefonnummer, Einkommen, Familienstand, Anzahl der Kinder, aktueller Standort, Internetbrowserverlauf, Accountnamen von anderen sozialen Medien und von Dritten erhaltene Daten); Gefühl der Verletzung der Privatsphäre durch folgende Institutionen: Google, Facebook, Staatliche Behörden, Universitätsforscher; allgemeine Datenschutzbedenken.

Welle 3:

Besitz von Smartphone, Handy, PC, Tablet und/oder E-Book-Reader; Social-Media-Nutzung: Account mit Benutzernahme und Passwort bei ausgewählten Anbietern (Google, Facebook, Twitter, LinkedIn, Xing); Vertrauen in Institutionen (Google, Facebook, Bundesamt für Statistik, Universitätsforscher) im Hinblick auf den Schutz persönlicher Daten; allgemeines Personenvertrauen; Bekanntheit der Datenschutz-Grundverordnung (DSGVO) der EU; Wissenstest: Ziele der DSGVO (offen); Besorgnis über Privatsphäre im Allgemeinen; Verständlichkeit von auszugweise wiedergegebenen Inhalten der Datenschutz-Grundverordnung (DSGVO) der EU (bzw. zu Fluggastrechten bei Nichtbeförderung und Flugverspätungen); geschätzte Popularität von Smartphones (Anteil der Smartphonebesitzer je 100 erwachsene Deutsche); Wiederholung der Frage nach dem Vertrauen in Datenerfassungsunternehmen (Google, Facebook) im Hinblick auf den Schutz personenbezogener Daten sowie zum allgemeinen Personenvertrauen; Bereitschaft zum Datenaustausch durch Google (bzw. Facebook oder das Statistische Bundesamt) für Forschungszwecke (bzw. für kommerzielle Zwecke).

Demographie: Geschlecht; Alter (Geburtsjahr); Bundesland; Schulbildung; berufliche Qualifikation.

Zusätzlich verkodet wurde: laufende Nummer; Befragten ID; Experimentalgruppen DSGVO Info; Dauer (Reaktionszeit in Sekunden); Gerätetyp, mit dem der Fragebogen ausgefüllt wurde.

Der Fragebogen beinhaltete auch zwei Experimente, eines über die Auswirkungen von DSGVO-bezogenen Informationen auf das Vertrauen in Datenerfassungsunternehmen und eines über den Komfort des Datenaustauschs mit verschiedenen Unternehmen aus verschiedenen Gründen.

Purpose - Data sharing is key for replication and re-use in empirical research. Scientific journals can play a central role by establishing data policies and providing technologies. This paper analyzes the factors which influence data sharing by investigating journal data policies and the behavior of authors in sociology. Design/methodology/approach - The websites of 140 sociology journals were consulted to check their data policy. The results are compared with similar studies from political science and economics. A broad selection of articles published in five selected journals over a period of two years are examined to determine whether authors really cite and share their data and the factors which are related to this. Findings - Although only a few sociology journals have explicit data policies, most journals make reference to a common policy supplied by their association of publishers. Among the journals selected, relatively few articles provide data citations and even fewer make data available - this is true both for journals with and without data policy. But authors writing for journals with higher impact factors and with data policies are more likely to cite data and to make it really accessible. Originality/value - No study of journal data policies has been undertaken to date for the domain of sociology. A comparison of authors' behaviors regarding data availability, data citation, and data accessibility for journals with or without a data policy provides useful information about the factors which improve data sharing.

Discusses how to overcome EU-US tensions in the area of personal data sharing under rubric of post-9/11 counterterrorism. The politicized nature of EU integration in the fields of counterterrorism & organized crime fighting is noted, along with how the US federal structure problematizes the establishment of a coherent interagency & intergovernmental strategy for addressing that issue. Although there has been improved transatlantic cooperation, it is suggested that long-term prospects for transatlantic information sharing are not so promising. The problem of guaranteeing protection of private data is addressed before looking at the deleterious impact that the Treaty of Lisbon would have on EU security cooperation & data sharing with the US. It is then contended that proper implementation of the US-EU Agreement on Mutual Legal Assistance could substantially improve transatlantic security cooperation. It is suggested that the MLAT could provide the US with the appropriate strategic approach to counterterrorism & crime fighting. Further, MLAT can improve cooperation & set future standards of judicial cooperation internationally, while also fostering the creation of genuinely international, integrated task forces. D. Edelman

This study draws on interviews with forty-nine members of a biomedical research community in the UK that is involved in negotiating data sharing and access. During an interview, an interviewee used the words "ethical moment" to describe a confrontation between collaborators in relation to data sharing. In this article, I use this as a lens for thinking about relations between "the conceptual and the empirical" in a way that allows both analyst and actor to challenge the status quo and consider other ethical possibilities. Drawing on actor network theory (ANT), I approach "the empirical" using the concepts of controversy and ontological uncertainty as methodological tools to tackle the problem of ethics. I suggest that these concepts also provide a bridge for understanding the ontological structure of the virtual and the actual, as described in Deleuze's Difference and Repetition. While other science and technology studies scholars have sought to draw on Deleuze, this article addresses the integration of ethics and empirical research. It arises as a critical reaction to existing treatments of this problem as found in empirical ethics, especially in the sociology of bioethics, and indirectly in ANT texts.

Introduction to B2G data sharing Data sharing is a key enabler of growth, employment, and competitiveness for Europe and the Digital Single Market envisaged by the European Union. The non-rivalrous nature of data, combined with technological innovations such as the availability of big data analysis and artificial intelligence applications, enable maximising the value of data. Re-using data can save costs, time and lives. The benefits of data re-use are not reserved to the private sector. In fact, to become more cost-efficient and provide effective services for citizens, public sector bodies can benefit greatly from data sharing and need to exploit the potential of new data sources. This data can be sourced from the private sector, academia, NGOs or the public sector itself. Much of the data generated in the public sector is already made open for re-use, encouraged by the Directive on Public Sector Information (PSI). However, there is also data that cannot be made open because of sensitivity or confidentiality. This data can only be shared under special conditions and to a restricted and controlled set of users in order to leverage their value. An example of a value is insight into the behavioural patterns of citizens and businesses across social, political, historical or environmental factors. This insight can help public sector organisations understand, evaluate, predict and prepare for certain situations and scenarios, for example: Understanding commuting patterns to support urban planning, road safety, and traffic management, as well as environmental protection. Additional insight into a population's health conditions, diagnosis, and medical treatments can improve public health care and lead to a more effective response to epidemics. Market monitoring and payment patterns can help detect fraud and increase consumer protection. In addition, there are legal, technical and organisational factors that must be considered when setting up a framework for data sharing between businesses and public organisations. In ...

Despite widespread support from policy makers, funding agencies, and scientific journals, academic researchers rarely make their research data available to others. At the same time, data sharing in research is attributed a vast potential for scientific progress. It allows the reproducibility of study results and the reuse of old data for new research questions. Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher's point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients . Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration. We conclude that research data cannot be regarded a knowledge commons, but research policies that better incentivize data sharing are needed to improve the quality of research results and foster scientific progress.

Data sharing is key for replication and re-use in empirical research. Scientific journals can play a central role by establishing data policies and providing technologies. In this study factors of influence for data sharing are analyzed by investigating journal data policies and author behavior in sociology. The websites of 140 journals from sociology were consulted to check their data policy. The results are compared with similar studies from political science and economics. For five selected journals with a broad variety all articles from two years are examined to see if authors really cite and share their data, and which factors are related to this.

This issue of the Journal of Empirical Research on Human Research Ethics highlights the ethical issues that arise when researchers conducting projects in low- and middle-income countries seek to share the data they produce. Although sharing data is considered a best practice, the barriers to doing so are considerable and there is a need for guidance and examples. To that end, the authors of this article reviewed the articles in this special issue to identify challenges common to the five countries and to offer some practical advice to assist researchers in navigating this "uncharted territory," as some termed it. Concerns around informed consent, data management, data dissemination, and validation of research contributions were cited frequently as particularly challenging areas, so the authors focused on these four topics with the goal of providing specific resources to consult as well as examples of successful projects attempting to solve many of the problems raised.