Prefigurative Post-Politics as Strategy:The Case of Government-Led Blockchain Projects

Critically engaging with literature on post-politics, blockchain and algorithmic governance, and drawing also on knowledge gained from undertaking a three-year empirical study, the purpose of this article is to better understand the transformative capacity of government-led blockchain projects. Analysis of a diversity of empirical material, which was guided by a digital ethnography approach, is used to support the furthering of the existing debate on the nature of the post-political as a condition and/or strategy. Through these theoretical and empirical explorations, the article concludes that while the post-political represents a contingent political strategy by governmental actors, it could potentially impose an algorithmically enforced post-political ‘condition’ for the citizen. It is argued that the design, features and mechanisms of government-led projects are deliberately and strategically used to delimit a citizens’ political agency. In order to address this scenario, we argue that there is a need not only to analyse and contribute to the algorithmic design of blockchain projects (i.e. the affordances and constraints they set), but also to the metapolitical narrative underpinning them (i.e. the political imaginaries underlying the various government-led projects)

Invest to Save: Report and Recommendations of the NSF-DELOS Working Group on Digital Archiving and Preservation

Digital archiving and preservation are important areas for research and development, but there is no agreed upon set of priorities or coherent plan for research in this area. Research projects in this area tend to be small and driven by particular institutional problems or concerns. As a consequence, proposed solutions from experimental projects and prototypes tend not to scale to millions of digital objects, nor do the results from disparate projects readily build on each other. It is also unclear whether it is worthwhile to seek general solutions or whether different strategies are needed for different types of digital objects and collections. The lack of coordination in both research and development means that there are some areas where researchers are reinventing the wheel while other areas are neglected. Digital archiving and preservation is an area that will benefit from an exercise in analysis, priority setting, and planning for future research. The WG aims to survey current research activities, identify gaps, and develop a white paper proposing future research directions in the area of digital preservation. Some of the potential areas for research include repository architectures and inter-operability among digital archives; automated tools for capture, ingest, and normalization of digital objects; and harmonization of preservation formats and metadata. There can also be opportunities for development of commercial products in the areas of mass storage systems, repositories and repository management systems, and data management software and tools.

Big Data in the Oil and Gas Industry: A Promising Courtship

The energy industry remains one of the highest money-producing and investment industries in the world. The United States’ own economic stability depends greatly on the stability of oil and gas prices. Various factors affect the amount of money that will continue to be invested in producing oil. A main disadvantage to the oil and gas industry is its lack of technological adaptation. This weakens the industry because the surest measures are not currently being taken to produce oil in optimally efficient, safe, and cost-effective ways. Big data has gained global recognition as an opportunity to gather large volumes of information in real-time and translate data sets into actionable insights. In a low commodity price environment, saving time, reducing costs, and improving safety are crucial outcomes that can be realized using machine learning in oil and gas operations. Big data provides the opportunity to use unsupervised learning. For example, with this approach, engineers can predict oil wells’ optimal barrels of production given the completion data in a specific area. However, a caveat to utilizing big data in the oil and gas industry is that there simply is neither enough physical data nor data velocity in the industry to be properly referred to as “big data.” Big data, as it develops, will nonetheless significantly change the energy business in the future, as it already has in various other industries.Petroleum and Geosystems Engineerin

Cadastral Systems Re-engineering in Urban Zimbabwe

Land is undoubtedly the most important resource in any country as it contributes to economic  development. The cadastre is a component of the land administration system (LAS) that is crucial for  managing land. It is thus of importance for a nation to have both a functional cadastral system for  determining parcel boundaries and a functional cadastral information system, for managing the land  parcels. The cadastral survey system and cadastre in Zimbabwe are largely manual with even the  lodgement of completed surveys for examination and approval still analogue. This has an impact on the  time it takes to complete a land transaction. Land can ideally drive the economy yet part of the value is  lost due to lengthy land transaction procedures. The land administration system is supposed to consist of value adding processes in which several actors interact in a workflow which creates new or transfers parcels. This workflow is associated with transaction costs, part of which can be employed for  maintenance of the cadastral information system. This article presents business processes for the land development process in Zimbabwe but focusing on City of Gweru (CoG) and City of Mutare (CoM)  municipalities as the major organisations under study. Municipalities in Zimbabwe are governed by the Regional Town and Country Planning Act, so such a single process and workflow model can fit into the cadastral information system of all municipalities in Zimbabwe with insignificant changes. The broader scope of this study is towards the design of a conceptual schema for automating the land administration system and particularly, the cadastre component, for municipalities in Zimbabwe. This study presents the workflows for the current land development system with CoG and CoM as the current focal points. Information on current automation efforts or reforms by other major municipalities to include Bulawayo, Kadoma and Kariba is also presented. The overall theme of this paper is to discuss cadastral reform through automation of cadastral processes in municipalities

An approach toward function allocation between humans and machines in space station activities

Basic guidelines and data to assist in the allocation of functions between humans and automated systems in a manned permanent space station are provided. Human capabilities and limitations are described. Criteria and guidelines for various levels of automation and human participation are described. A collection of human factors data is included

An Intelligent Data Mining System to Detect Health Care Fraud

The chapter begins with an overview of the types of healthcare fraud. Next, there is a brief discussion of issues with the current fraud detection approaches. The chapter then develops information technology based approaches and illustrates how these technologies can improve current practice. Finally, there is a summary of the major findings and the implications for healthcare practice