Open data ecosystems are expected to bring many advantages, such as stimulating citizen participation and innovation. However, scant attention has been given to what constitutes an open data ecosystem. The objective of this paper is to provide an overview of essential elements of open data ecosystems for enabling easy publication and use of open data. To achieve this objective, the literature has been reviewed and a scenario about the publication and use of open data has been analyzed. It was found that various applications, tools and portals are available which together can form an ecosystem. The best functionalities of this ecosystem can be selected and utilized by open data providers and users. To create an open data ecosystem at least four key elements should be captured, namely, 1) releasing and publishing open data on the internet, 2) searching, finding, evaluating and viewing data and their related licenses, 3) cleansing, analyzing, enriching, combining, linking and visualizing data and 4) interpreting and discussing data and providing feedback to the data provider and other stakeholders. Furthermore, to integrate the ecosystem elements and to let them act as an integrated whole, there should be three additional elements 5) user pathways showing directions for how open data can be used, 6) a quality management system and 7) different types of metadata to be able to connect the elements.
The global energy system is undergoing a major transition, and in energy planning and decision-making across governments, industry and academia, models play a crucial role. Because of their policy relevance and contested nature, the transparency and open availability of energy models and data are of particular importance. Here we provide a practical how-to guide based on the collective experience of members of the Open Energy Modelling Initiative (Openmod). We discuss key steps to consider when opening code and data, including determining intellectual property ownership, choosing a licence and appropriate modelling languages, distributing code and data, and providing support and building communities. After illustrating these decisions with examples and lessons learned from the community, we conclude that even though individual researchers' choices are important, institutional changes are still also necessary for more openness and transparency in energy research
This study analyzes the evolution of the research field of industrial symbiosis (IS). We elucidate its embedding in industrial ecology (IE), trace the development of research themes, and reveal the evolution of the research network through analysis of the core literature and journals that appeared from 1997 to 2012 by citation analysis, cocitation analysis, and network analysis.In the first period (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005), IS research held a minority share in the IE literature. The research revolved around the concept of IS, the assessment of eco-industrial park projects, and the establishment of waste treatment and recycling networks. In the second period (2006)(2007)(2008)(2009)(2010)(2011)(2012), diverse research approaches and theories enriched the field, which has led to a maturation in theory building. Our findings clearly illustrate that IS evolved from practiceoriented research toward coherent theory building through a systematic underpinning and linking of diverse topics. As scientific attention shifted from exploring a phenomenon to elucidating underlying mechanisms, IS knowledge found worldwide practical implementation. The coauthorship network shows that the academic communities of IS are distributed worldwide and that international collaboration is widespread.Through bibliometric and network analysis of IS, we have created a systemic, quantitative image of the evolution of the IS research field and community, which gives IS researchers an underpinned overview of the IS research and may help them to identify new directions and synergy in worldwide research.Volume 18, Number 2 and Laybourn (2012, 31) proposed a new definition emphasizing that "IS engages diverse organizations in a network to foster ecoinnovation and long-term culture change. Creating and sharing knowledge through the network yields mutually profitable transactions for novel sourcing of required inputs, value-added destinations for non-product outputs, and improved business and technical processes."As with the interdiscipline of IE, it appears that the IS idea and subsequent research started from the inspiration of biology and ecology as well as from a drive to develop more-sustainable production systems (e.g., Allenby and Cooper 1994;
SummaryIndustrial ecology (IE) is an ambitious field of study where we seek to understand systems using a wide perspective ranging from the scale of molecules to that of the planet. Achieving such a holistic view is challenging and requires collecting, processing, curating, and sharing immense amounts of data and knowledge.We are not capable of fully achieving this due to the current state of tools used in IE and current community practices. Although we deal with a vastly interconnected world, we are not so good at efficiently interconnecting what we learn about it. This is not a problem unique to IE, and other fields have begun to use tools supported by the World Wide Web to meet these challenges.We discuss these sets of tools and illustrate how community driven data collection, processing, curation, and sharing is allowing people to achieve more than ever before. In particular, we discuss standards that have been created to allow for interlinking of data dispersed across multiple Web sites. This is currently visible in the Linking Open Data initiative, which among others contains interlinked datasets from the U.S. and U.K. governments, biology databases, and Wikipedia. Since the types of technologies and standards involved are outside the normal scope of work by many industrial ecologists, we attempt to explain the relevance, implications, and benefits through a discussion of many real examples currently on the Web.From these, we discuss several best practices, which can be enabling factors for how IE and the community can more efficiently and effectively meet its ambitions-an agenda for
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