Data development for international research—Phase I: International conflict and national characteristics

In 1986 developers and users of quantitative data in international and comparative politics organized to maintain, extend, and develop major datasets and to provide a stronger basis for coordinating data‐related activities. National Science Foundation funding established for a three‐year period Data Development for International Research. Its first phase (DDIR‐I) focused on improving datasets on both national capabilities and international conflict; and generating renewed efforts to better the data collections on internation events and international political economy. DDIR‐I's work, now virtually complete, augmented the quantity and quality of this national data resource and set the stage for another NSF‐funded project on internation event data (DDIR‐II). A final report on DDIR‐II is forthcoming in summer 1994.     

Violence Against Civilians: A Disaggregated Analysis

Disaggregated approaches to conflict research have led to new insights into the patterns and processes of political violence in developing countries. This article uses the most comprehensive subnational political violence data (ACLED) to observe where and when violence against civilians occurs within civil wars. Several new conclusions are evident from an event-based analysis of civilian violence: retribution or collateral damage are poor explanations for attacks on the unarmed. Instead, civilians are targeted because they are accessible; rebel groups kill more civilians, often in an attempt to create new frontlines for conflict. However, governments are also responsible for high rates of civilian death, yet they often “contract” this violence out to militias. This analysis confirms that there are multiple violent groups within civil war spaces, and small opposition groups commit higher levels of violence against civilians in local spaces. The strength of a violent group compared to its competition shapes how much civilian violence it commits. The results suggest that theories that emphasize civilian support and retribution as a basis for violence against civilians have overlooked the importance of how multiple violent opposition groups compete within civil wars, and how civilians suffer as a result.     

Intraobserver Error in Macromorphoscopic Trait Data, ,

As part of a much larger investigation into the use of macromorphoscopic trait data by forensic anthropologists to estimate ancestry from unidentified skeletal remains, we conducted a fourteen‐year (2002–2016) intraobserver error study. Motivated by the development of a large macromorphoscopic database―which will potentially utilize data collected in 2002―quantification of observer error, the impact of technological improvements in macromorphoscopic trait data collection and observer experience is necessary. To maximize comparisons between the two samples, ten macromorphoscopic traits were assessed. Results revealed three patterns of error relating to observer experience, the introduction of new technologies, and error inherent in the method. Overall, this study found the effect of error on macromorphoscopic trait analysis could be predicted and did not significantly impact their utility.     

Longitudinal Analysis of Links Between Bullying Victimization and Psychosomatic Maladjustment in Swedish Schoolchildren

Cross-sectional studies of bullying mask variability in categories of and persistence of bullying victimization. Longitudinal, individual-level data offers a greater insight into schoolchildren’s psychosomatic maladjustment as a consequence of bullying. Swedish schoolchildren (n = 3,349), with unique identifiers, in 44 schools (4th–9th grade), answered a questionnaire at baseline and 1-year follow-up. Longitudinal trends for nonvictims (88%), ceased victims (4.7%), new victims (5.7%), and continuing victims (1.6%) revealed that new victims had the largest decrease in well-being; continuing victims had a smaller though not significant decrease; while ceased victims showed a small, (nonsignificant) increase in well-being over the measurement period. It was also discovered that children not bullied at baseline but bullied subsequently, differed, at baseline, from their never-bullied peers through lower levels of overall well-being. It is argued that this finding has implications for prevention strategies.     

Ownership of personal data in the Internet of Things

This article analyses, defines, and refines the concepts of ownership and personal data to explore their compatibility in the context of EU law. It critically examines the traditional dividing line between personal and non-personal data and argues for a strict conceptual separation of personal data from personal information. The article also considers whether, and to what extent, the concept of ownership can be applied to personal data in the context of the Internet of Things (IoT). This consideration is framed around two main approaches shaping all ownership theories: a bottom-up and top-down approach. Via these dual lenses, the article reviews existing debates relating to four elements supporting introduction of ownership of personal data, namely the elements of control, protection, valuation, and allocation of personal data. It then explores the explanatory advantages and disadvantages of the two approaches in relation to each of these elements as well as to ownership of personal data in IoT at large. Lastly, this article outlines a revised approach to ownership of personal data in IoT that may serve as a blueprint for future work in this area and inform regulatory and policy debates.     

Are ‘pseudonymised’ data always personal data? Implications of the GDPR for administrative data research in the UK

There has naturally been a good deal of discussion of the forthcoming General Data Protection Regulation. One issue of interest to all data controllers, and of particular concern for researchers, is whether the GDPR expands the scope of personal data through the introduction of the term ‘pseudonymisation’ in Article 4(5). If all data which have been ‘pseudonymised’ in the conventional sense of the word (e.g. key-coded) are to be treated as personal data, this would have serious implications for research. Administrative data research, which is carried out on data routinely collected and held by public authorities, would be particularly affected as the sharing of de-identified data could constitute the unconsented disclosure of identifiable information.Instead, however, we argue that the definition of pseudonymisation in Article 4(5) GDPR will not expand the category of personal data, and that there is no intention that it should do so. The definition of pseudonymisation under the GDPR is not intended to determine whether data are personal data; indeed it is clear that all data falling within this definition are personal data. Rather, it is Recital 26 and its requirement of a ‘means reasonably likely to be used’ which remains the relevant test as to whether data are personal. This leaves open the possibility that data which have been ‘pseudonymised’ in the conventional sense of key-coding can still be rendered anonymous. There may also be circumstances in which data which have undergone pseudonymisation within one organisation could be anonymous for a third party. We explain how, with reference to the data environment factors as set out in the UK Anonymisation Network's Anonymisation Decision-Making Framework.     

A comparison of data protection legislation and policies across the EU

Although the protection of personal data is harmonized within the EU by Directive 95/46/EC and will be further harmonized by the General Data Protection Regulation (GDPR) in 2018, there are significant differences in the ways in which EU member states implemented the protection of privacy and personal data in national laws, policies, and practices. This paper presents the main findings of a research project that compares the protection of privacy and personal data in eight EU member states: France, Germany, the UK, Ireland, Romania, Italy, Sweden, and the Netherlands. The comparison focuses on five major themes: awareness and trust, government policies for personal data protection, the applicable laws and regulations, implementation of those laws and regulations, and supervision and enforcement.The comparison of privacy and data protection regimes across the EU shows some remarkable findings, revealing which countries are frontrunners and which countries are lagging behind on specific aspects. For instance, the roles of and interplay between governments, civil rights organizations, and data protections authorities vary from country to country. Furthermore, with regard to privacy and data protection there are differences in the intensity and scope of political debates, information campaigns, media attention, and public debate. New concepts like privacy impact assessments, privacy by design, data breach notifications and big data are on the agenda in some but not in all countries. Significant differences exist in (the levels of) enforcement by the different data protection authorities, due to different legal competencies, available budgets and personnel, policies, and cultural factors.     

DATA REGULATION IN THE INTERNET OF THINGS

The reflections on data regulation in the internet of things (IoT) in this paper provide an overview of the different conceptions and legal problems of “data property rights.” Beginning with an overview of the existing and possible applications of the future IoT (in particular, smart cars), this paper describes the legal concerns that may arise because of increased commercialization of object-generated data. The author uses German and European Union law to illustrate the legal complexities, solutions, and shortcomings. He demonstrates how and to what extent these issues are covered by traditional data protection regulations and highlights the conceptual blind spots of these regulations. He then contrasts the data protection paradigm (de lege lata) with the idea of a general erga omnes data property right (de lege ferenda) and describes the most common understanding of such a right, that is, a data producers’ property right. Against the background of the possible economic advantages of general data property rights, the paper discusses conceptual problems and constitutional concerns. In conclusion, the author rejects the idea of a general data property right.