Networks of SLGOs: from systems interoperability to organizational cooperability

E-Government doesn’t concern only technological innovation in Public Administration, but most of all organizational innovation through the adoption of organizational models enabled by the use of ICTs. One model of this kind, that in countries characterized by a high number of Small Local Government Organizations (SLGOs) can be adopted also to reduce the administrative fragmentation, is inter-organizational cooperation among SLGOs. This is the model the Italian National Center for Information Technology in Public Administration (CNIPA) adopted in the action plan to promote E-Government in Local Public Administration in Italy. However, inter-organizational cooperation requires the partners to interoperate, at least in the areas which are the object of the cooperation. One possibility which guarantees interoperability of different organizations consists in the adoption of a shared cooperative environment. Depending on how binding are the conditions which define it, the cooperative environment can determine different levels of interoperability, up to organizational interoperability (cooperability). In the case of cooperation among organizations which can be heterogeneous, one of the conditions defining the cooperative environment is the sharing of an “enterprise model” for the cooperation. In the paper we describe some of the conditions that define a cooperative environment and introduce a system for the description and the classification of different forms of intercommunal cooperation for services provision

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

Department of Homeland Security Science and Technology Directorate: Developing Technology to Protect America

In response to a congressional mandate and in consultation with Department of Homeland Security's (DHS) Science and Technology Directorate (S&T), the National Academy conducted a review of S&T's effectiveness and efficiency in addressing homeland security needs. This review included a particular focus that identified any unnecessary duplication of effort, and opportunity costs arising from an emphasis on homeland security-related research. Under the direction of the National Academy Panel, the study team reviewed a wide variety of documents related to S&T and homeland security-related research in general. The team also conducted interviews with more than 200 individuals, including S&T officials and staff, officials from other DHS component agencies, other federal agencies engaged in homeland security-related research, and experts from outside government in science policy, homeland security-related research and other scientific fields.Key FindingsThe results of this effort indicated that S&T faces a significant challenge in marshaling the resources of multiple federal agencies to work together to develop a homeland security-related strategic plan for all agencies. Yet the importance of this role should not be underestimated. The very process of working across agencies to develop and align the federal homeland security research enterprise around a forward-focused plan is critical to ensuring that future efforts support a common vision and goals, and that the metrics by which to measure national progress, and make changes as needed, are in place

The role of use cases in development of a reference framework for interoperability of data exchange in agriculture

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Scenarios for the development of smart grids in the UK: literature review

Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid. It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers. The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.

Challenges and potential of the Semantic Web for tourism

The paper explores tourism challenges and potential of the Semantic Web from a theoretical and industry perspective. It first examines tourism business networks and explores a main theme of network interoperability - data standards- followed by technology deficiencies of Web 1.0 and 2.0 and Semantic Web solutions. It then explicates Semantic opportunities and challenges for tourism, including an industry perspective through a qualitative approach. Industry leaders considered that the new Web era was imminent and heralded benefits for supply and demand side interoperability, although management and technical challenges could impede progress and delay realisation

Simulation of the Long-Term Effects of Decentralized and Adaptive Investments in Cross-Agency Interoperable and Standard IT Systems

Governments have come under increasing pressure to promote horizontal flows of information across agencies, but investment in cross-agency interoperable and standard systems have been minimally made since it seems to require government agencies to give up the autonomies in managing own systems and its outcomes may be subject to many external and interaction risks. By producing an agent-based model using 'Blanche' software, this study provides policy-makers with a simulation-based demonstration illustrating how government agencies can autonomously and interactively build, standardize, and operate interoperable IT systems in a decentralized environment. This simulation designs an illustrative body of 20 federal agencies and their missions. A multiplicative production function is adopted to model the interdependent effects of heterogeneous systems on joint mission capabilities, and six social network drivers (similarity, reciprocity, centrality, mission priority, interdependencies, and transitivity) are assumed to jointly determine inter-agency system utilization. This exercise simulates five policy alternatives derived from joint implementation of three policy levers (IT investment portfolio, standardization, and inter-agency operation). The simulation results show that modest investments in standard systems improve interoperability remarkably, but that a wide range of untargeted interoperability with lagging operational capabilities improves mission capability less remarkably. Nonetheless, exploratory modeling against the varying parameters for technology, interdependency, and social capital demonstrates that the wide range of untargeted interoperability responds better to uncertain future states and hence reduces the variances of joint mission capabilities. In sum, decentralized and adaptive investments in interoperable and standard systems can enhance joint mission capabilities substantially and robustly without requiring radical changes toward centralized IT management.Public IT Investment, Interoperability, Standardization, Social Network, Agent-Based Modeling, Exploratory Modeling