Suchergebnisse

Today (Wednesday 27 March) we have published storm overflow (Event Duration Monitoring data) for the 2023 calendar year. Event Duration Monitors record the number and duration of spills from storm overflows. To view mapped data visit Storm Overflow Spill Frequency (arcgis.com) …

Part 1: Semantic Concepts and Open Data ; International audience ; Open Data is a current trend in sharing data on the Web. Public sector bodies maintain large amounts of data that, if re-used, could be a source of significant benefits. Therefore Open Government Data initiatives have been launched in many countries in order to increase availability of openly licensed and machine-readable government data. Because Open Data publishers face various challenges, methods for publication of Open Data are emerging. However these methods differ in focus, scope and structure which might complicate selection of a method that would suit specific needs of an organization. In this paper we discuss the possible benefits of constructing Open Data publication methods from a meta-model and we use the Software and Systems Process Engineering Meta-Model version 2.0 to analyze similarities and differences in structure of three Open Data publication methods.

During the past decade, the relevance of research data has been rising significantly and the free and open access not only to scientific results, but to research datasets has been identified as a key issue by the scientific community, funding agencies and the public. As a consequence, there is a dynamic coevolution of national and international guidelines on management of and open access to research data (e.g. Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities, G8 Open Data Charter, EU Horizon 2020 Guidelines, etc.) and the development of concepts to make data persistently accessible and citable products of research. Especially in permafrost and climate research, longterm observatories and world-wide monitoring programmes are essential to understand the impact of, e.g., permafrost thaw on the Earth climate system and consequently of climate change. Many datasets are online available, via data portals or databases like, e.g. at the National Snow and Ice Datacentre, the GTN-P Database, NORPERM, Fluxnet, etc., but often without the possibility to give the data providers recognition and acknowledgement for contributing data to a global network. During the past years, the publication of research datasets with assigned digital object identifier (DOI) has emerged as best practice for citable and persistent open access research data together with the deserved recognition of the data providers. An important step for the international acceptance and recognition of DOI-referenced data publication is the'Statement of Commitment'of the Coalition for Data Publication in the Earth and Space Sciences (COPDESS) that aims to promote joint policies and procedures for the publication and citation of data across Earth Science journals. Key commitments, signed by many publishers and data centres, are the acceptance of data citations within reference lists of research articles, the improvement of cross-references between journal articles and published datasets, and the strong recommendation to, whenever possible, store datasets in appropriate, theme-specific data repositories, in which data access and long-term preservation are guaranteed and datasets are accompanied by sufficient metadata to enable data reuse and discovery. A comprehensive data description is essential for data reuse. Data publication is mostly known as supplementary material to scientific articles. Very often, however, the data description in the journal article is not sufficient for data reuse leading to many published dataset not being used as much as they could be. To improve this, many disciplines have developed and are developing "Data Journals" that aim to publish scientific articles with the detailed description of datasets, data portals or data collections that will be published along with the datasets. There are different formats for articles in data journals, but all have in common that they lack of any scientific interpretation of the described datasets. For standalone publication of datasets where neither format is an option, accompanying data reports are a convenient and flexible tool for enhanced data description.

There is a lack of research concerning the factors influencing the success or failure of open data initiatives. Based on the results of two workshops, we provide a list of 47 success factors for open data publication and 18 success factors for open data use. We further use three case studies (ENGAGE, Open NY, and Open Vienna) to examine how the criticality of factors varies depending on the geographical level and other characteristics of the open data initiative. The cases, representing open data initiatives at city, regional and transnational levels, point at different categories of critical success factors. Our key conclusions are that 1) the criticality of the factors depends considerably on the context of the open data initiative; 2) a number of success factors appear to be more universally applicable than others; 3) the factors that are critical to all three cases are derived from many different success factor categories, which suggests that open data initiatives should adopt an interdisciplinary approach, and 4) further work is needed to detail the success factors for open data publication and use in other contexts.

Open Government Data (OGD) is a movement that has spread worldwide, enabling the publication of thousands of datasets on the Web, aiming to concretize transparency and citizen participatory governance. This initiative can create value by linking data describing the same phenomenon from different perspectives using the traditional Web and semantic web technologies. A framework of these technologies is linked data movement that guides the publication of data and their interconnection in a machine-readable means enabling automatic interpretation and exploitation. Nevertheless, Open Government Data publication as Linked Open Data (LOD) is not a trivial task due to several obstacles, such as data heterogeneity issues. Many works dealing with this transformation process have been published that need to be investigated thoroughly to deduce the general trends and the issues related to this field. The current work proposes a classification of existing methods dealing with OGD-LOD transformation and a synthesis study to highlight their main trends and challenges.

The provision and dissemination of Open Data is a flourishing concept, which is highly recognized and established in the government and public administrations domains. Typically, the actual data is served as static file downloads, such as CSV or PDF, and the established software solutions for Open Data are mostly designed to manage this kind of data. However, the rising popularity of the Internet of things and smart devices in the public and private domain leads to an increase of available real-time data, like public transportation schedules, weather forecasts, or power grid data. Such timely and extensive data cannot be used to its full potential when published in a static, file-based fashion. Therefore, we designed and developed Ronda - an open source platform for gathering, processing and publishing real-time Open Data based on industry-proven and established big data and data processing tools. Our solution easily enables Open Data publishers to provide real-time interfaces for heterogeneous data sources, fostering more sophisticated and advanced Open Data use cases. We have evaluated our work through a practical application in a production environment.