Open Environmental Platforms: Top-Level Components and Relevant Standards

We present our ideas of an open Information and Communication Technology (ICT) platform for monitoring, mapping and managing our environment. The envisioned solution bridges the gap between the Internet of Things, Content and Services, and highly specific applications, such as oil spill detection or marine monitoring. On the one hand, this environmental platform should be open to new technologies; on the other hand, it has to provide open standard interfaces to various application domains. We identify core components, standards, and needs for new standard development in ICT for environment. We briefly outline how our past and present activities contribute to the development of the desired open environmental platform. Future implementations shall contribute to sustainable developments in the environmental domain.JRC.DDG.H.6-Spatial data infrastructure

Evaluating pedagogical practices supporting collaborative learning for model-based system development courses

Model-based software development (MBSD) has been widely used in industry for its effectiveness of code generation, code reuse and system evolution. At different stages of the software lifecycle, models -- as opposed to actual code -- are used as abstractions to present software development artifacts. In a university software engineering curriculum, compared to other concrete and tangible courses, e.g., game and app development, these levels of abstraction are often difficult for students to understand, and further, to see models' usefulness in practice. This paper presents an evaluation of pedagogical practices supporting collaborative learning for MBSD courses from experiences of teaching them at University of Oslo. The focus is to answer two research questions: 1) What are the challenges and possibilities when using a collaborative learning approach for teaching modelling and architecture? 2) What are the challenges and benefits of having a holistic approach to MBSD courses in light of the requirements of academia and the needs of industry? The term “holistic” is understood 1) as an approach that involves human factors (users), technology and processes, 2) as an approach to teaching MBSD courses where modelling for Enterprise Architecture is taught together with System Architecture and Model-Driven Language Engineering. Empirical data was collected through interviews, questionnaires, and document analysis. The paper’s research results show that three different course perspectives (Modeling for Enterprise Architecture with Business Architecture, System Architecture and Model Driven Language Engineering) are essential parts of teaching modeling courses, and an industry field study shows that industry sees the potential of having junior architects to provide support to a team and solving basic architectural problems

Environmental Information Systems on the Internet: A Need for Change

The cost effective delivery of scientific and policy requirements is a key driver for the realization of global sustainability research, integrated assessment and supporting innovative systems. The next generation of geospatial information infrastructures is proposed as a possible solution. Still, questions such as ‘what does all this mean to environmental information systems’ and ‘what is expected to change’, have only partially been answered. In this paper, we describe the recent challenges for eEnvironment services in Europe, specify desired capabilities and derive according requirements. We identify affected stakeholder communities and depict their involvement in the overall value chain of environmental knowledge generation. Specific examples illustrate individual needs, while a derived description of the value chain indicates more general outcomes. Developmental requirements of future information systems are discussed. The presented work answers the questions above by bridging the gab between stakeholder needs, Information and Communication Technology (ICT) development and higher level concepts, such as Digital Earth and Future Internet.JRC.DDG.H.6-Spatial data infrastructure

Open Data, VGI and Citizen Observatories INSPIRE Hackathon

In 2016, the INSPIRE Conference hosted the first INSPIRE hackathon on volunteered geographic information and citizen observatories, also known as the INSPIRE Hackathon. The organisers, mostly representatives of European research and innovation projects, continued this activity with the next INSPIRE Conference in 2017. The INSPIRE Hackathon is a collaborative event for developers, researchers, designers and others interested in open data, volunteered geographic information and citizen observatories. The main driving force for the INSPIRE Hackathon is provided by experts from existing EU projects, and its primary objective is to share knowledge and experience between the participants and demonstrate to wider audiences the power of data and information supported by modern technologies and common standards, originating from INSPIRE, Copernicus, GEOSS and other initiatives. This paper describes the history and background of the INSPIRE Hackathon, the various INSPIRE-related hackathons already organised, supporting projects, the results of INSPIRE Hackathon 2017 and the authors’ vision of future activities

Mobile technologies and personalized environmental information for supporting sustainable mobility in Oslo: The citisense-mob approach

Abstract Urban and peri-urban growth is increasing world-wide and Europe is now one of the most urbanized continents in the world. Oslo is one of the fastest growing cities in Europe. This creates pressure on its infrastructure, including traffic and environmental urban quality. Additionally, vehicular traffic is a major contributor to CO 2 emissions, which impacts climate change. It is recognized that air quality is a major factor for human health however, although different measures have been implemented, improving air quality and lowering carbon emissions still remains an unsolved problem in Oslo. The main objective of Citi-Sense-MOB is to demonstrate how using innovative technology to continuously measure environmental data at the road level combined with innovative Information and Communication Technologies (ICT) can help to create a dynamic city infrastructure for realtime city management, access to personalized environmental information and sustainable development. The output from the project will be mobile services for citizens and authorities based on the use of near real-time data on air quality and CO 2 emissions at road level. The societal importance of these services arises from a need to mitigate the effects of air pollution and climate change, and to combat respiratory diseases related to traffic-related air pollution. In order to motivate citizens to use the information generated by the project, Citi-Sense-MOB will provide them with personalized environmental information, as for instance alerting systems when pollution levels exceed a critical threshold. Customized information will also be provided to authorities consisting of detailed air quality maps at high spatial resolution and an evaluation of possibilities to reduce CO 2 emissions by improving driving practices in public urban fleets

Technical Research Priorities for Big Data

To drive innovation and competitiveness, organisations need to foster the development and broad adoption of data technologies, value-adding use cases and sustainable business models. Enabling an effective data ecosystem requires overcoming several technical challenges associated with the cost and complexity of management, processing, analysis and utilisation of data. This chapter details a community-driven initiative to identify and characterise the key technical research priorities for research and development in data technologies. The chapter examines the systemic and structured methodology used to gather inputs from over 200 stakeholder organisations. The result of the process identified five key technical research priorities in the areas of data management, data processing, data analytics, data visualisation and user interactions, and data protection, together with 28 sub-level challenges. The process also highlighted the important role of data standardisation, data engineering and DevOps for Big Data