Data standardization

With data rapidly becoming the lifeblood of the global economy, the ability to improve its use significantly affects both social and private welfare. Data standardization is key to facilitating and improving the use of data when data portability and interoperability are needed. Absent data standardization, a “Tower of Babel” of different databases may be created, limiting synergetic knowledge production. Based on interviews with data scientists, this Article identifies three main technological obstacles to data portability and interoperability: metadata uncertainties, data transfer obstacles, and missing data. It then explains how data standardization can remove at least some of these obstacles and lead to smoother data flows and better machine learning. The Article then identifies and analyzes additional effects of data standardization. As shown, data standardization has the potential to support a competitive and distributed data collection ecosystem and lead to easier policing in cases where rights are infringed or unjustified harms are created by data-fed algorithms. At the same time, increasing the scale and scope of data analysis can create negative externalities in the form of better profiling, increased harms to privacy, and cybersecurity harms. Standardization also has implications for investment and innovation, especially if lock-in to an inefficient standard occurs. The Article then explores whether market-led standardization initiatives can be relied upon to increase welfare, and the role governmental-facilitated data standardization should play, if at all

Culture-based artefacts to inform ICT design: foundations and practice

Cultural aspects frame our perception of the world and direct the many different ways people interact with things in it. For this reason, these aspects should be considered when designing technology with the purpose to positively impact people in a community. In this paper, we revisit the foundations of culture aiming to bring this concept in dialogue with design. To inform design with cultural aspects, we model reality in three levels of formality: informal, formal, and technical, and subscribe to a systemic vision that considers the technical solution as part of a more complex social system in which people live and interact. In this paper, we instantiate this theoretical and methodological view by presenting two case studies of technology design in which culture-based artefacts were employed to inform the design process. We claim that as important as including issues related to culture in the ICT design agenda—from the conception to the development, evaluation, and adoption of a technology—is the need to support the design process with adequate artefacts that help identifying cultural aspects within communities and translating them into sociotechnical requirements. We argue that a culturally informed perspective on design can go beyond an informative analysis, and can be integrated with the theoretical and methodological framework used to support design, throughout the entire design process

Visions and Challenges in Managing and Preserving Data to Measure Quality of Life

Health-related data analysis plays an important role in self-knowledge, disease prevention, diagnosis, and quality of life assessment. With the advent of data-driven solutions, a myriad of apps and Internet of Things (IoT) devices (wearables, home-medical sensors, etc) facilitates data collection and provide cloud storage with a central administration. More recently, blockchain and other distributed ledgers became available as alternative storage options based on decentralised organisation systems. We bring attention to the human data bleeding problem and argue that neither centralised nor decentralised system organisations are a magic bullet for data-driven innovation if individual, community and societal values are ignored. The motivation for this position paper is to elaborate on strategies to protect privacy as well as to encourage data sharing and support open data without requiring a complex access protocol for researchers. Our main contribution is to outline the design of a self-regulated Open Health Archive (OHA) system with focus on quality of life (QoL) data.Comment: DSS 2018: Data-Driven Self-Regulating System

Preparing for the Use of Big Data in Denmark’s Waste Management Sector

This project explored the challenges and opportunities associated with prospective implementations of big data analytics in Denmark’s waste industry. We found that while some waste management companies collect detailed data, they do not use or share their data adequately. We identified that, to begin implementing big data into Denmark’s waste industry, companies must: expand data collection on internal operations and waste per household; develop better data management systems; and review technical, ethical, and legal practices surrounding personal data on waste

Diverse perceptions of smart spaces

This is the era of smart technology and of ‘smart’ as a meme, so we have run three workshops to examine the ‘smart’ meme and the exploitation of smart environments. The literature relating to smart spaces focuses primarily on technologies and their capabilities. Our three workshops demonstrated that we require a stronger user focus if we are advantageously to exploit spaces ascribed as smart: we examined the concept of smartness from a variety of perspectives, in collaboration with a broad range of contributors. We have prepared this monograph mainly to report on the third workshop, held at Bournemouth University in April 2012, but do also consider the lessons learned from all three. We conclude with a roadmap for a fourth (and final) workshop, which is intended to emphasise the overarching importance of the humans using the spac

Shared Benefits and Information Privacy: What Determines Smart Meter Technology Adoption?

An unexplored gap in IT adoption research concerns the positive role of shared benefits even when personal information is exposed. To explore the evaluation paradigm of shared benefits versus the forfeiture of personal information, we analyze how utility consumers use smart metering technology (SMT). In this context, utility companies can monitor electricity usage and directly control consumers’ appliances to disable them during peak load conditions. Such information could reveal consumers’ habits and lifestyles and, thus, stimulating concerns about their privacy and the loss of control over their appliances. Responding to calls for theory contextualization, we assess the efficacy of applying extant adoption theories in this emergent context while adding the perspective of the psychological ownership of information. We use the factorial survey method to assess consumers’ intentions to adopt SMT in the presence of specific conditions that could reduce the degree of their privacy or their control over their appliances and electricity usage data. Our findings suggest that, although the shared benefit of avoiding disruptions in electricity supply (brownouts) is a significant factor in electricity consumers’ decisions to adopt SMT, concerns about control and information privacy are also factors. Our findings extend the previous adoption research by exploring the role of shared benefits and could provide utility companies with insights into the best ways to present SMT to alleviate consumers’ concerns and maximize its adoption

Emerging Opportunities: Monitoring and Evaluation in a Tech-Enabled World

Various trends are impacting on the field of monitoring and evaluation in the area of international development. Resources have become ever more scarce while expectations for what development assistance should achieve are growing. The search for more efficient systems to measure impact is on. Country governments are also working to improve their own capacities for evaluation, and demand is rising from national and community-based organizations for meaningful participation in the evaluation process as well as for greater voice and more accountability from both aid and development agencies and government.These factors, in addition to greater competition for limited resources in the area of international development, are pushing donors, program participants and evaluators themselves to seek more rigorous – and at the same time flexible – systems to monitor and evaluate development and humanitarian interventions.However, many current approaches to M&E are unable to address the changing structure of development assistance and the increasingly complex environment in which it operates. Operational challenges (for example, limited time, insufficient resources and poor data quality) as well as methodological challenges that impact on the quality and timeliness of evaluation exercises have yet to be fully overcome