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Doxing refers to the intentional public release by a third party of personal data without consent, often with the intent to humiliate, intimidate, harass, or punish the individual concerned. Intuitively, it is tempting to condemn doxing as a crude form of cyber violence that weaponizes personal data. When it is used as a strategy of resistance by the powerless to hold the powerful accountable, however, a more nuanced understanding is called for. This chapter focuses on the doxing phenomenon in Hong Kong, where doxing incidents against police officers and their family members have skyrocketed since 2019 (a 75-fold increase over 2018). It contends that doxing for political purposes is closely related to digital vigilantism, signifying a loss of confidence in the ruling authority and a yearning for an alternative form of justice. The chapter therefore argues that public interest should be recognized as a legal defense in doxing cases when those discharging or entrusted with public duty are the targets. Equally, it is important to confine the categories of personal data disclosed to information necessary to reveal the alleged wrongdoer or wrongdoing. Only in this way can a fair balance be struck between privacy, freedom of expression, and public interest.

Models of Child Health Appraised (MOCHA) was a wide-ranging, multi-disciplinary and multi-method study that aimed to identify the best models of provision of primary care for the children of the European Union. The research has identified two main conclusions: (1) The depth of interdependency of health, economy and society. Primary care needs to be an active partner in public debate about current child health concerns. It should orientate more effectively in addressing wider societal influences on child health through advocacy and collaborative intersectoral public health approaches with those agencies responsible for public and community health if it is to address effectively issues such as childhood obesity, mental health and vaccine hesitancy. As part of this, it needs to address its workforce composition and skills, not least in two-way communication. (2) The European Community has many visions and commitments to children and child health policies, but their effectiveness is largely unfulfilled. The Commission can strengthen its impact on children’s health and healthcare services within current remits and resources by focusing on a number of key fields: planned and structured research, providing insight into optimal human resources and skills in child primary care, developing and using ethical means of listening to children’s views, remedying the invisibility of children in data, measuring the quality of primary care from a child-centric perspective, understanding the economics of investing in children’s health, developing e-health standards and evaluation, collaborative and harmonised use of downloaded research databases, understanding and respecting children’s rights and equity, and appreciating and allowing for children’s evolving autonomy as they grow up. An optimal model of primary care for children is proactive, inclusive, corporately linked, based on and providing robust evidence, and respects the wider determinants of health and children’s involvement in their health trajectory.

Low productivity in construction is typically blamed on the seemingly complex and chaotic nature of construction, which emerges as the stakeholders do not have an adequate picture of the evolving situation. The ever-increasing volume of situation data owing to the recent advances in IoT devices and reality capture platforms provide a unique opportunity to capture the actual situation data of construction projects accurately at a fraction of the cost compared to manual status tracking and reporting. This paper aims to investigate the concept of a situation picture, challenges in collecting situation data and its benefits.

Empirical data is collected through interviews in California and Finland, and by organizing workshops.

We contribute to literature on managing operational information by defining the concept of a situation picture in the context of construction, specifically from the blue-collar’s perspective during on-site activities. We present the key components of a conceptual information model that represents a situation picture in construction.

The applicability of conceptual information model of situation picture is not tested in practice, but the model will provide a starting point for research to comprehensively integrate social and digital information exchange for improving workflow.

The paper claims that designing and building comprehensive information management infrastructure would contribute to solving the problems of low productivity, quality and safety in construction projects.

Research on situation picture and situation awareness is scarce in the context of construction. The study links various information management technologies and practices to actual construction productivity.

Advances in Big Data, artificial Intelligence and data-driven innovation bring enormous benefits for the overall society and for different sectors. By contrast, their misuse can lead to data workflows bypassing the intent of privacy and data protection law, as well as of ethical mandates. It may be referred to as the ‘creep factor’ of Big Data, and needs to be tackled right away, especially considering that we are moving towards the ‘datafication’ of society, where devices to capture, collect, store and process data are becoming ever-cheaper and faster, whilst the computational power is continuously increasing. If using Big Data in truly anonymisable ways, within an ethically sound and societally focussed framework, is capable of acting as an enabler of sustainable development, using Big Data outside such a framework poses a number of threats, potential hurdles and multiple ethical challenges. Some examples are the impact on privacy caused by new surveillance tools and data gathering techniques, including also group privacy, high-tech profiling, automated decision making and discriminatory practices. In our society, everything can be given a score and critical life changing opportunities are increasingly determined by such scoring systems, often obtained through secret predictive algorithms applied to data to determine who has value. It is therefore essential to guarantee the fairness and accurateness of such scoring systems and that the decisions relying upon them are realised in a legal and ethical manner, avoiding the risk of stigmatisation capable of affecting individuals’ opportunities. Likewise, it is necessary to prevent the so-called ‘social cooling’. This represents the long-term negative side effects of the data-driven innovation, in particular of such scoring systems and of the reputation economy. It is reflected in terms, for instance, of self-censorship, risk-aversion and lack of exercise of free speech generated by increasingly intrusive Big Data practices lacking an ethical foundation. Another key ethics dimension pertains to human-data interaction in Internet of Things (IoT) environments, which is increasing the volume of data collected, the speed of the process and the variety of data sources. It is urgent to further investigate aspects like the ‘ownership’ of data and other hurdles, especially considering that the regulatory landscape is developing at a much slower pace than IoT and the evolution of Big Data technologies. These are only some examples of the issues and consequences that Big Data raise, which require adequate measures in response to the ‘data trust deficit’, moving not towards the prohibition of the collection of data but rather towards the identification and prohibition of their misuse and unfair behaviours and treatments, once government and companies have such data. At the same time, the debate should further investigate ‘data altruism’, deepening how the increasing amounts of data in our society can be concretely used for public good and the best implementation modalities.

Purpose – The purpose of this research is to study the ecological developments that are growing rapidly and are complemented by technological developments that make ecology a discipline which is able to collaborate, integrate, and use data for the development of science.

Design/Methodology/Approach – The method involves integration, analysis, and conclusion, drawing knowledge dissemination from heterogeneous ecological data that make the ecological research so complex requiring an approach to simplify the problem.

Findings – The data involved in ecology are very complex and diverse and spread from various sources, which are not mutually integrated so that a structured arrangement is required through the arrangement of computer-based data management.

Research Limitations/Implications – Eco-informatics is one of the options to manage the data, settings, and transform it into information and knowledge.

Large-scale data analytics have raised a number of ethical concerns. Many of these were introduced in a seminal paper by boyd and Crawford and have been developed since by others (boyd & Crawford, 2012; Lagoze, 2014; Martin, 2015; Mittelstadt, Allo, Taddeo, Wachter, & Floridi, 2016). One such concern which is frequently recognised but under-analysed is the focus on correlation of data rather than on the causative relationship between data and results. Advocates of this approach dismiss the need for an understanding of causation, holding instead that the correlation of data is sufficient to meet our needs. In crude terms, this position holds that we no longer need to know why X+Y=Z. Merely acknowledging that the pattern exists is enough.

In this chapter, the author explores the ethical implications and challenges surrounding a focus on correlation over causation. In particular, the author focusses on questions of legitimacy of data collection, the embedding of persistent bias, and the implications of future predictions. Such concerns are vital for understanding the ethical implications of, for example, the collection and use of ‘big data’ or the covert access to ‘secondary’ information ostensibly ‘publicly available’. The author’s conclusion is that by failing to consider causation, the short-term benefits of speed and cost may be countered by ethically problematic scenarios in both the short and long term.

This chapter reflects on the understanding of the phenomenon known as Smart Industry, Industry 4.0, fourth industrial revolution, and many other labels. It does so by reflecting on the issue of terminology, as well as the existing diversity regarding the description of the phenomenon. The issue of meaning is addressed by assessing the results from Culot, Nassimbeni, Orzes, and Sartor (2020) and Habraken and Bondarouk (2019) which are, subsequently, used to develop a workable description. Findings from the two assessed studies raise the question of whether a workable construction of the phenomenon is to be understood as the key technologies or the distinctive developments? A question without a definitive answer, but I will present my view by taking inspiration from the manner in which the prior industrial revolutions are commonly understood. This leads to a, still multifaceted though, more focused understanding of the phenomenon. The insights, formulated proposition and developed model stemming from the reflection of terminology and meaning of the phenomenon helps move the current technology-related phenomenon forward. They assist with the establishment of well-documented papers. A critical aspect if we aim to understand how management will look like in the era of this phenomenon.

Purpose – This study aims to design and build a wireless supervisory control and data acquisition (SCADA) system based on Protocol AX.25 with the aim of monitoring the performance of several parameters in Microhydro Power Plant (MHPP). This system can monitor several MHPP parameters such as voltage, current, frequency, and turbine rotation so that it can be accessed directly at one central location.

Design/Methodology/Approach – The design is done by taking into account the real parameters that exist in the MHPP. Some parameters that become the main object to see the performance of MHPP are voltage, current, frequency, and turbine rotation. The voltage generated by the MHPP must be adjusted to the voltage supplied by State Electricity Company to the consumer, including the phase used. The resulting stream should also be monitored for power to be adjusted to the turbine spin. The generator frequency is kept stable according to the standard frequency of the State Electricity Company generator.

Findings – The remote terminal unit (RTU) system has been simulated using 2 ACS712 current sensors, voltage sensor, zero crossing point, frequency sensor, and rotation sensor functionalized to monitor MHPP parameters. The AX.25 protocol has been applicable in the wireless SCADA network for monitoring the performance of MHPP by embedding in KYL-1020UA transceiver radio using the 433 MHz frequency and the audio frequency shift keying modulation system. Radio transmitter KYL-1020UA has been successfully simulated to send data from sensors to display on the computer through SCADA built applications. The data changes in the RTU section can be displayed properly on the graphic user interface in accordance with the existing display at the MHPP location.

Research Limitations/Implications – There are only two RTUs that will be connected to communicate, in this case MHPP-1 with callsign “RTU-001” and MHPP-2 with callsign “RTU-002.” While the existing devices in the data access section parameters MHPP as master station with callsign “MSSCADA” monitoring the performance of parameters sent from the RTU. There is no collision or error in data transmission. Baudrate is varied at 1,200 bps, 2,400 bps, 4,800 bps, and 9,600 bps for effective throughput calculation and AX.25 protocol efficiency. The transmission distance is varied at 100 m, 200 m, 300 m, and 500 m to see the bit error rate with baudrate 1,200 bps and 9,600 bps.

Practical Implications – This product is expected to be applied to several MHPP locations in Aceh Province so that its monitoring system is more centralized and efficient.

Originality/Value – This research if for the efficient monitoring of several MHPP located far apart and can be monitored in one central location so that operators do not have to be located at the plant site.

This chapter summarises the role of EU actions in supporting healthcare policies in the EU Member States, both looking at implemented actions and describing current priorities for the future. It argues that these coordinated actions can be beneficial for EU Member States by helping them to avoid duplication of effort and to attain economies of scale. Moreover, data sharing with proper safeguards can unleash vast amount of ‘learning what works’ both for medical treatments and for healthcare sustainability measures. The need for this common learning appears ever more urgent while facing the health and economic consequences of the present pandemic.