Envisioning Digital Europe 2030: Scenarios for ICT in Future Governance and Policy Modelling

The report Envisioning Digital Europe 2030 is the result of research conducted by the Information Society Unit of IPTS as part of the CROSSROAD Project - A Participative Roadmap on ICT research on Electronic Governance and Policy Modelling (www.crossroad-eu.net ). After outlining the purpose and scope of the report and the methodological approach followed, the report presents the results of a systematic analysis of societal, policy and research trends in the governance and policy modelling domain in Europe. These analyses are considered central for understanding and roadmapping future research on ICT for governance and policy modelling. The study further illustrates the scenario design framework, analysing current and future challenges in ICT for governance and policy modelling, and identifying the key impact dimensions to be considered. It then presents the scenarios developed at the horizon 2030, including the illustrative storyboards representative of each scenario and the prospective opportunities and risks identified for each of them. The scenarios developed are internally consistent views of what the European governance and policy making system could have become by 2030 and of what the resulting implications for citizens, business and public services would be. Finally, the report draws conclusions and presents the proposed shared vision for Digital Europe 2030, offering also a summary of the main elements to be considered as an input for the future development of the research roadmap on ICT for governance and policy modelling.JRC.DDG.J.4-Information Societ

Automatic Identification of Structural Process Weaknesses – Experiences with Semantic Business Process Modeling in the Financial Sector

Business process reengineering (BPR) has been a core research topic for at least the last twenty years. As banks have realized the need to look on their business in a process-oriented way, they have been engaged in numerous business process reengineering projects to make their organizations more efficient. However, the success of BPR projects in banks varies significantly and it remains a challenge to systematically discover weaknesses in business process landscapes. Based on the Semantic Business Process Modeling Language (SBPML) this paper introduces a new approach for pattern-based automatic process model analysis, with a focus on identifying structural process weaknesses such as organizational process fragmentation, possibly unnecessary process complexity or multiple resource usage or other process inefficiencies. Additionally, this approach also allows for a benchmarking of different process path alternatives in the same process or among different processes. In this article, this approach is applied and evaluated in the financial sector, but it can possibly also be used in other domains. It contributes to a more efficient and more effective identification of possible weaknesses in process models in comparison to today’s manual analysis of process models

The Once-Only Principle

This open access State-of-the-Art Survey describes and documents the developments and results of the Once-Only Principle Project (TOOP). The Once-Only Principle (OOP) is part of the seven underlying principles of the eGovernment Action Plan 2016-2020. It aims to make the government more effective and to reduce administrative burdens by asking citizens and companies to provide certain standard information to the public authorities only once. The project was horizontal and policy-driven with the aim of showing that the implementation of OOP in a cross-border and cross-sector setting is feasible. The book summarizes the results of the project from policy, organizational, architectural, and technical points of view

Data Ingredients: smart disclosure and open government data as complementary tools to meet policy objectives. The case of energy efficiency.

Open government data are considered a key asset for eGovernment. One could argue that governments can influence other types of data disclosure, as potential ingredients of innovative services. To discuss this assumption, we took the example of the U.S. 'Green Button' initiative – based on the disclosure of energy consumption data to each user – and analysed 36 energy-oriented digital services reusing these and other data, in order to highlight their set of inputs. We find that apps suggesting to a user a more efficient consumption behaviour also benefit from average retail electricity cost/price information; that energy efficiency 'scoring' apps also need, at least, structured and updated information on buildings performance; and that value-added services that derive insights from consumption data frequently rely on average energy consumption information. More in general, most of the surveyed services combine consumption data, open government data, and corporate data. When setting sector-specific agendas grounded on data disclosure, public agencies should therefore consider (contributing) to make available all three layers of information. No widely acknowledged initiatives of energy consumption data disclosure to users are being implemented in the EU. Moreover, browsing EU data portals and websites of public agencies, we find that other key data ingredients are not supplied (or, at least, not as open data), leaving room for possible improvements in this arena

Managing uncertainty in integrated environmental modelling:the UncertWeb framework

Web-based distributed modelling architectures are gaining increasing recognition as potentially useful tools to build holistic environmental models, combining individual components in complex workflows. However, existing web-based modelling frameworks currently offer no support for managing uncertainty. On the other hand, the rich array of modelling frameworks and simulation tools which support uncertainty propagation in complex and chained models typically lack the benefits of web based solutions such as ready publication, discoverability and easy access. In this article we describe the developments within the UncertWeb project which are designed to provide uncertainty support in the context of the proposed ‘Model Web’. We give an overview of uncertainty in modelling, review uncertainty management in existing modelling frameworks and consider the semantic and interoperability issues raised by integrated modelling. We describe the scope and architecture required to support uncertainty management as developed in UncertWeb. This includes tools which support elicitation, aggregation/disaggregation, visualisation and uncertainty/sensitivity analysis. We conclude by highlighting areas that require further research and development in UncertWeb, such as model calibration and inference within complex environmental models

Towards a Standard-based Domain-specific Platform to Solve Machine Learning-based Problems

Machine learning is one of the most important subfields of computer science and can be used to solve a variety of interesting artificial intelligence problems. There are different languages, framework and tools to define the data needed to solve machine learning-based problems. However, there is a great number of very diverse alternatives which makes it difficult the intercommunication, portability and re-usability of the definitions, designs or algorithms that any developer may create. In this paper, we take the first step towards a language and a development environment independent of the underlying technologies, allowing developers to design solutions to solve machine learning-based problems in a simple and fast way, automatically generating code for other technologies. That can be considered a transparent bridge among current technologies. We rely on Model-Driven Engineering approach, focusing on the creation of models to abstract the definition of artifacts from the underlying technologies

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse