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This chapter analyzes the compliance of some category of Open Data in Politics with EU General Data Protection Regulation (GDPR) requirements. After clarifying the legal basis of this framework, with specific attention to the processing procedures that conform to the legitimate interests pursued by the data controller, including open data licenses or anonymization techniques, that can result in partial application of the GDPR, but there is no generic guarantee, and, as a consequence, an appropriate process of analysis and management of risks is required.

This paper aims to design a secure and seamless system that ensures quick sharing of health-care data to improve the privacy of sensitive health-care data, the efficiency of health-care infrastructure, effective treatment given to patients and encourage the development of new health-care technologies by researchers. These objectives are achieved through the proposed system, a “privacy-aware data tagging system using role-based access control for health-care data.”

Health-care data must be stored and shared in such a manner that the privacy of the patient is maintained. The method proposed, uses data tags to classify health-care data into various color codes which signify the sensitivity of data. It makes use of the ARX tool to anonymize raw health-care data and uses role-based access control as a means of ensuring only authenticated persons can access the data.

The system integrates the tagging and anonymizing of health-care data coupled with robust access control policies into one architecture. The paper discusses the proposed architecture, describes the algorithm used to tag health-care data, analyzes the metrics of the anonymized data against various attacks and devises a mathematical model for role-based access control.

The paper integrates three disparate topics – data tagging, anonymization and role-based access policies into one seamless architecture. Codifying health-care data into different tags based on International Classification of Diseases 10th Revision (ICD-10) codes and applying varying levels of anonymization for each data tag along with role-based access policies is unique to the system and also ensures the usability of data for research.

This study aims to report on an automatic deidentification system for labeling and obfuscating personally identifiable information (PII) in student-generated text.

The authors evaluate the performance of their deidentification system on two data sets of student-generated text. Each data set was human-annotated for PII. The authors evaluate using two approaches: per-token PII classification accuracy and a simulated reidentification attack design. In the reidentification attack, two reviewers attempted to recover student identities from the data after PII was obfuscated by the authors’ system. In both cases, results are reported in terms of recall and precision.

The authors’ deidentification system recalled 84% of student name tokens in their first data set (96% of full names). On the second data set, it achieved a recall of 74% for student name tokens (91% of full names) and 75% for all direct identifiers. After the second data set was obfuscated by the authors’ system, two reviewers attempted to recover the identities of students from the obfuscated data. They performed below chance, indicating that the obfuscated data presents a low identity disclosure risk.

The two data sets used in this study are not representative of all forms of student-generated text, so further work is needed to evaluate performance on more data.

This paper presents an open-source and automatic deidentification system appropriate for student-generated text with technical explanations and evaluations of performance.

Previous study on text deidentification has shown success in the medical domain. This paper develops on these approaches and applies them to text in the educational domain.

This paper aims to explore the issues, the role of research data management (RDM) as a mechanism for implementing open research data and the role and opportunities for records managers. The open data agenda is premised on making as much data as possible open and available. However, in the context of open research data there are methodological, ethical and practical issues with this premise.

Two collaborative research projects focusing on qualitative health data were conducted. “DATUM for Health” designed and delivered a tailored RDM skills training programme for postgraduate research students in health studies. “DATUM in Action” was an action research project between researchers from information sciences, health, mathematics and computing, looking at planning and implementing RDM.

Three key issues emerged about what research data is appropriate to make open/accessible for sharing and reuse: re-using qualitative data conflicts with some of the epistemological and methodological principles of qualitative research; there are ethical concerns about making data obtained from human participants open, which are not completely addressed by consent and anonymisation; many research projects are small scale and the costs of preparing and curating data for open access can outweigh its value. In exploring these issues, the authors advocate the need for effective appraisal skills and researcher-focused RDM with records managers playing a useful role.

The findings come from two small-scale qualitative projects in health studies. Further exploration of these issues is required.

Records managers have new crucial opportunities in the open data and RDM contexts, bringing their expertise and experience in managing a wider range of data and information. They can help realise the benefits of multiple perspectives (researcher, data manager, records manager and archivist) on open research data.

Researcher-focused RDM offers a mechanism for implementing open research data.

It raises complex issues around open research data not found in the records management literature, highlights the need for researcher-focussed RDM and research data appraisal skills and a not yet fully recognised role for records managers.

Research data management (RDM) is gaining a lot of momentum in the present day and rightly so. Research data are the core of any research study. The findings and conclusions of a study are entirely dependent on the research data. Traditional publishing did not focus on the presentation of data, along with the publications such as research monographs and especially journal articles, probably because of the difficulties involved in managing the research data sets. The current day technology, however, has helped in making this task easier. The purpose of this paper is to present a conceptual framework for managing research data at the institutional level.

This paper discusses the significance and advantages of sharing research data. In the spirit of open access to publications, freeing research data and making it available openly, with minimal restrictions, will help in not only furthering research and development but also avoiding duplication of efforts. The issues and challenges involved in RDM at the institutional level are discussed.

A conceptual framework for RDM at the institutional level is presented. A model for a National Repository of Open Research Data (NRORD) is also proposed, and the workflow of the functioning of NRORD is also presented.

The framework clearly presents the workflow of the data life-cycle in its various phases right from its creation, storage, organization and sharing. It also attempts to address crucial issues in RDM such as data privacy, data security, copyright and licensing. The framework may help the institutions in managing the research data life-cycle in a more efficient and effective manner.

The continuous advancements in wearable sensing technologies enable the easy collection and publishing of visual lifelog data. The widespread adaptation of visual lifelog technologies would have the potential to pose challenges for ensuring the personal privacy of subjects and bystanders in lifelog data. This paper presents preliminary findings from a study of lifeloggers with the aim of better understanding their concerns regarding privacy in lifelog data.

In this study, we have collected a visual dataset of 64,837 images from 25 lifelogging participants over a period of two days each, and we conducted an interactive session (face to face conversation) with each participant in order to capture their concerns when sharing the lifelog data across three specified categories (i.e. Private (Only for Me), Semi-Private (Family/Friends) and Public).

In general, we found that participants tend to err on the side of conservative privacy settings and that there is a noticeable difference in what different participants are willing to share. In summary, we found that the categories of images that the participants wished to be kept private included personally identifiable information and professional information; categories of images that could be shared with family/friends include family moments or content related to daily routine lifestyle, and other visual lifelog data could potentially be made public).

We analysed the potential differences in the willingness of 25 participants to share data. In addition, reasons for being a volunteer to collect lifelog data and how the lifelogging device affected the lifestyle of the lifelogger are analysed. Based on the findings of this study, we propose a set of challenges for the anonymisation of lifelog data that should be solved when supporting lifelog data sharing.

Smart cities require data governance to articulate data sharing and use among relevant stakeholders. Given the lack of a comprehensive examination of this research topic, this study aims to review data governance publications to detect and categorize endeavors backing up data sharing in smart cities.

A systematic literature review was conducted, and 568 academic and professional sources were identified, but finally, only 10 relevant papers were selected.

Results reveal that data governance must be based on well-defined mechanisms, procedures and roles to achieve accountability and responsibility in a multi-actor environment. Moreover, data governance should be adapted to address power imbalances among all interested parties.

The main limitation is the list of sources considered for the literature review. However, this study provides a holistic overview for researchers and professionals willing to know more about smart city data sharing.

This review identifies the data governance approaches supporting data sharing in smart cities, analyzes their data dimension, enhances the state-of-the-art literature on this topic and suggests possible areas for future research.

Information dissemination has become a means of transparency for governments to enable the visions of e-government and smart government, and eventually gain, among others, the trust of various stakeholders such as citizens and enterprises. Information dissemination, on the other hand, may increase the chance of privacy breaches, which can undermine those stakeholders’ trust and thus the objectives of transparency. Moreover, fear of potential privacy breaches compels information disseminators to share minimum or no information. The purpose of this study is to address these contending issues of information disseminations, i.e. privacy versus transparency, when disseminating judicial information to gain (public) trust. Specifically, the main research questions are: What is the nature of the aforementioned “privacy–transparency” problem and how can we approach and address this class of problems?

To address these questions, the authors have carried out an explorative case study by reconsidering and analyzing a number of information dissemination cases within their research center for the past 10 years, reflecting upon the whole design research process, consulting peers through publishing a preliminary version of this contribution and embedding the work in an in-depth literature study on research methodologies, wicked problems and e-government topics.

The authors show that preserving privacy while disseminating information for transparency purposes is a typical wicked problem, propose an innovative designerly model called transitional action design research (TADR) to address the class of such wicked problems and describe three artifacts which are designed, intervened and evaluated according to the TADR model in a judicial research organization.

Classifying the privacy transparency problem in the judicial settings as wicked is new, the proposed designerly model is innovative and the realized artifacts are deployed and still operational in a real setting.

The purpose of this study is to generate knowledge about the use of smart campus tools to improve the effective and efficient use of campuses. Many universities are facing a challenge in attuning their accommodation to organisational demand. How can universities invest their resources as effectively as possible and not in space that will be poorly utilized? The hypothesis of this paper is that by using smart campus tools, this problem can be solved.

To answer the research question, previous survey at 13 Dutch universities was updated and compared with a survey of various universities and other organizations. The survey consisted of interviews with structured and semi-structured questions, which resulted in a unified output for 27 cases.

Based on the output of the cases, the development of smart campus tools at Dutch universities was compared to that of international universities and other organizations. Furthermore, the data collection led to insights regarding the reasons for initiating smart campus tools, user and management information, costs and benefits and foreseen developments.

Although the use of smart tools in practice has gained significant momentum in the past few years, research on the subject is still very technology-oriented and not well-connected to facility management and real estate management. This paper provides an overview of the ways in which universities and organizations are currently supporting their users, improving the use of their buildings and reducing their energy footprint through the use of smart tools.

This research aims to explore the research data ethics governance framework and collaborative network to optimize research data ethics governance practices, to balance the relationship between data development and utilization, open sharing, data security and to reduce the ethical risks that may arise from data sharing and utilization.

This study explores the framework and collaborative network of research data ethics policies by using the UK as an example. 78 policies from the UK government, university, research institution, funding agency, publisher, database, library and third-party organization are obtained. Adopting grounded theory (GT) and social network analysis (SNA), Nvivo12 is used to analyze these samples and summarize the research data ethics governance framework. Ucinet and Netdraw are used to reveal collaborative networks in policy.

Results indicate that the framework covers governance context, subject and measure. The content of governance context contains context description and data ethics issues analysis. Governance subject consists of defining subjects and facilitating their collaboration. Governance measure includes governance guidance and ethics governance initiatives in the data lifecycle. The collaborative network indicates that research institution plays a central role in ethics governance. The core of the governance content are ethics governance initiatives, governance guidance and governance context description.

This research provides new insights for policy analysis by combining GT and SNA methods. Research data ethics and its governance are conceptualized to complete data governance and research ethics theory.

A research data ethics governance framework and collaborative network are revealed, and actionable guidance for addressing essential aspects of research data ethics and multiple subjects to confer their functions in collaborative governance is provided.

This study analyzes policy text using qualitative and quantitative methods, ensuring fine-grained content profiling and improving policy research. A typical research data ethics governance framework is revealed. Various stakeholders' roles and priorities in collaborative governance are explored. These contribute to improving governance policies and governance levels in both theory and practice.