Exploring Blockchain Governance

Blockchain systems continue to attract significant interest from both practitioners and researchers. What is more, blockchain systems come in various types, such as cryptocurrencies or as inter-organizational systems in business networks. As an example of a cryptocurrency, Bitcoin, one of the most prominent blockchain systems to date and born at the time of a major financial crisis, spearheaded the promise of relying on code and computation instead of a central governing entity. Proponents would argue that Bitcoin stood the test of time, as Bitcoin continues to operate to date for over a decade. However, these proponents overlook the never-ending, heated debates “behind the scenes” caused by diverging goals of central actors, which led to numerous alternative systems (forks) of Bitcoin. To accommodate these actors’ interests in the pursuit of their common goal is a tightrope act, and this is where this dissertation commences: blockchain governance. Based on the empirical examples of various types and application domains of blockchain systems, it is the goal of this dissertation to 1) uncover governance patterns by showing, how blockchain systems are governed, 2) derive governance challenges faced or caused by blockchain systems, and, consequently, to 3) contribute to a better understanding to what blockchain governance is. This dissertation includes four parts, each of these covering different thematical areas: In the first part, this dissertation focuses on obtaining a better understanding of blockchain governance’s context of reference by studying blockchain systems from various application domains and system types, for example, led by inter-organizational networks, states, or an independent group of actors. The second part, then, focuses on a blockchain as an inter-organizational system called “cardossier”, a project I was involved in, and its governance as a frame of reference. Hereupon, for one, I report on learnings from my project involvement in the form of managerial guidelines, and, for two, I report on structural problems within cardossier, and problems caused by membership growth and how they can be resolved. The third part focuses on a wider study of blockchains as inter-organizational systems, where I summarize findings of an analysis of 19 blockchain consortia. The findings, for one, answer the question of why blockchain consortia adopt blockchain technology, and, for two, show internal and external challenges these systems faced to derive managerial recommendations. The fourth and last part studies blockchain governance’s evolution and contributes an analysis of blockchain’s governance features and its contrast to established modes of governance. These four parts, altogether, have scientific value as they increase our understanding on blockchain governance. Consequently, this dissertation contributes to the body of knowledge on modes of governance, distributed system governance, and blockchain governance in general. I do so, by grounding the concept of blockchain governance in empirical detail, showing how these systems are governed on various application domains and system types, and by studying empirical challenges faced or caused by these systems. This approach is relevant and necessary, as blockchain systems in general, but particularly outside of cryptocurrencies, mostly still are in pursuit of a sustainable blockchain governance. As blockchains can be expected to continue to mature, the upcoming years offer very fruitful ground for empirical research along the empirical insights and theoretical lines shown in this dissertation

The Trouble With Big Data

This book is available as open access through the Bloomsbury Open programme and is available on www.bloomsburycollections.com. It is funded by Trinity College Dublin, DARIAH-EU and the European Commission. This book explores the challenges society faces with big data, through the lens of culture rather than social, political or economic trends, as demonstrated in the words we use, the values that underpin our interactions, and the biases and assumptions that drive us. Focusing on areas such as data and language, data and sensemaking, data and power, data and invisibility, and big data aggregation, it demonstrates that humanities research, focussing on cultural rather than social, political or economic frames of reference for viewing technology, resists mass datafication for a reason, and that those very reasons can be instructive for the critical observation of big data research and innovation

Archives, Access and Artificial Intelligence

Digital archives are transforming the Humanities and the Sciences. Digitized collections of newspapers and books have pushed scholars to develop new, data-rich methods. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Digital Humanities have moved from the fringe to the center of academia. Yet, the path from the appraisal of records to their analysis is far from smooth. This book explores crossovers between various disciplines to improve the discoverability, accessibility, and use of born-digital archives and other cultural assets

Archives, Access and Artificial Intelligence: Working with Born-Digital and Digitized Archival Collections

Digital archives are transforming the Humanities and the Sciences. Digitized collections of newspapers and books have pushed scholars to develop new, data-rich methods. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Digital Humanities have moved from the fringe to the center of academia. Yet, the path from the appraisal of records to their analysis is far from smooth. This book explores crossovers between various disciplines to improve the discoverability, accessibility, and use of born-digital archives and other cultural assets

Digital Transformation of Learning Organizations

This open access volume provides insight into how organizations change through the adoption of digital technologies. Opportunities and challenges for individuals as well as the organization are addressed. It features four major themes: 1. Current research exploring the theoretical underpinnings of digital transformation of organizations. 2. Insights into available digital technologies as well as organizational requirements for technology adoption. 3. Issues and challenges for designing and implementing digital transformation in learning organizations. 4. Case studies, empirical research findings, and examples from organizations which successfully adopted digital workplace learning

Computer Vision and Architectural History at Eye Level:Mixed Methods for Linking Research in the Humanities and in Information Technology

Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valuableinsights are gained into the past and the present as they also provide a foundation for designing the future. Given that our understanding of the past is limited by the inadequate availability of data, the article demonstrates that advanced computer tools can help gain more and well-linked data from the past. Computer vision can make a decisive contribution to the identification of image content in historical photographs. This application is particularly interesting for architectural history, where visual sources play an essential role in understanding the built environment of the past, yet lack of reliable metadata often hinders the use of materials. The automated recognition contributes to making a variety of image sources usable forresearch.<br/

Computer Vision and Architectural History at Eye Level:Mixed Methods for Linking Research in the Humanities and in Information Technology

Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valuableinsights are gained into the past and the present as they also provide a foundation for designing the future. Given that our understanding of the past is limited by the inadequate availability of data, the article demonstrates that advanced computer tools can help gain more and well-linked data from the past. Computer vision can make a decisive contribution to the identification of image content in historical photographs. This application is particularly interesting for architectural history, where visual sources play an essential role in understanding the built environment of the past, yet lack of reliable metadata often hinders the use of materials. The automated recognition contributes to making a variety of image sources usable forresearch.<br/