An Architecture for Integrated Intelligence in Urban Management using Cloud Computing

With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates the application of cloud capacity to support the information, communication and decision making needs of a wide variety of stakeholders in the complex business of the management of urban and regional development. The complexity lies in the interactions and impacts embodied in the concept of the urban-ecosystem at various governance levels. This highlights the need for more effective integrated environmental management systems. This paper offers a user-orientated approach based on requirements for an effective management of the urban-ecosystem and the potential contributions that can be supported by the cloud computing community. Furthermore, the commonality of the influence of the drivers of change at the urban level offers the opportunity for the cloud computing community to develop generic solutions that can serve the needs of hundreds of cities from Europe and indeed globally.Comment: 6 pages, 3 figure

Global-Scale Resource Survey and Performance Monitoring of Public OGC Web Map Services

One of the most widely-implemented service standards provided by the Open Geospatial Consortium (OGC) to the user community is the Web Map Service (WMS). WMS is widely employed globally, but there is limited knowledge of the global distribution, adoption status or the service quality of these online WMS resources. To fill this void, we investigated global WMSs resources and performed distributed performance monitoring of these services. This paper explicates a distributed monitoring framework that was used to monitor 46,296 WMSs continuously for over one year and a crawling method to discover these WMSs. We analyzed server locations, provider types, themes, the spatiotemporal coverage of map layers and the service versions for 41,703 valid WMSs. Furthermore, we appraised the stability and performance of basic operations for 1210 selected WMSs (i.e., GetCapabilities and GetMap). We discuss the major reasons for request errors and performance issues, as well as the relationship between service response times and the spatiotemporal distribution of client monitoring sites. This paper will help service providers, end users and developers of standards to grasp the status of global WMS resources, as well as to understand the adoption status of OGC standards. The conclusions drawn in this paper can benefit geospatial resource discovery, service performance evaluation and guide service performance improvements.Comment: 24 pages; 15 figure

Enhancing Energy Production with Exascale HPC Methods

High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the Intel Corporation, which enabled us to obtain the presented experimental results in uncertainty quantification in seismic imagingPostprint (author's final draft

Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)

The Helmholtz Association funded the "Large-Scale Data Management and Analysis" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities

Management and Visualisation of Non-linear History of Polygonal 3D Models

The research presented in this thesis concerns the problems of maintenance and revision control of large-scale three dimensional (3D) models over the Internet. As the models grow in size and the authoring tools grow in complexity, standard approaches to collaborative asset development become impractical. The prevalent paradigm of sharing files on a file system poses serious risks with regards, but not limited to, ensuring consistency and concurrency of multi-user 3D editing. Although modifications might be tracked manually using naming conventions or automatically in a version control system (VCS), understanding the provenance of a large 3D dataset is hard due to revision metadata not being associated with the underlying scene structures. Some tools and protocols enable seamless synchronisation of file and directory changes in remote locations. However, the existing web-based technologies are not yet fully exploiting the modern design patters for access to and management of alternative shared resources online. Therefore, four distinct but highly interconnected conceptual tools are explored. The first is the organisation of 3D assets within recent document-oriented No Structured Query Language (NoSQL) databases. These "schemaless" databases, unlike their relational counterparts, do not represent data in rigid table structures. Instead, they rely on polymorphic documents composed of key-value pairs that are much better suited to the diverse nature of 3D assets. Hence, a domain-specific non-linear revision control system 3D Repo is built around a NoSQL database to enable asynchronous editing similar to traditional VCSs. The second concept is that of visual 3D differencing and merging. The accompanying 3D Diff tool supports interactive conflict resolution at the level of scene graph nodes that are de facto the delta changes stored in the repository. The third is the utilisation of HyperText Transfer Protocol (HTTP) for the purposes of 3D data management. The XML3DRepo daemon application exposes the contents of the repository and the version control logic in a Representational State Transfer (REST) style of architecture. At the same time, it manifests the effects of various 3D encoding strategies on the file sizes and download times in modern web browsers. The fourth and final concept is the reverse-engineering of an editing history. Even if the models are being version controlled, the extracted provenance is limited to additions, deletions and modifications. The 3D Timeline tool, therefore, implies a plausible history of common modelling operations such as duplications, transformations, etc. Given a collection of 3D models, it estimates a part-based correspondence and visualises it in a temporal flow. The prototype tools developed as part of the research were evaluated in pilot user studies that suggest they are usable by the end users and well suited to their respective tasks. Together, the results constitute a novel framework that demonstrates the feasibility of a domain-specific 3D version control

Methods Included:Standardizing Computational Reuse and Portability with the Common Workflow Language

A widely used standard for portable multilingual data analysis pipelines would enable considerable benefits to scholarly publication reuse, research/industry collaboration, regulatory cost control, and to the environment. Published research that used multiple computer languages for their analysis pipelines would include a complete and reusable description of that analysis that is runnable on a diverse set of computing environments. Researchers would be able to easier collaborate and reuse these pipelines, adding or exchanging components regardless of programming language used; collaborations with and within the industry would be easier; approval of new medical interventions that rely on such pipelines would be faster. Time will be saved and environmental impact would also be reduced, as these descriptions contain enough information for advanced optimization without user intervention. Workflows are widely used in data analysis pipelines, enabling innovation and decision-making for the modern society. In many domains the analysis components are numerous and written in multiple different computer languages by third parties. However, lacking a standard for reusable and portable multilingual workflows, then reusing published multilingual workflows, collaborating on open problems, and optimizing their execution would be severely hampered. Moreover, only a standard for multilingual data analysis pipelines that was widely used would enable considerable benefits to research-industry collaboration, regulatory cost control, and to preserving the environment. Prior to the start of the CWL project, there was no standard for describing multilingual analysis pipelines in a portable and reusable manner. Even today / currently, although there exist hundreds of single-vendor and other single-source systems that run workflows, none is a general, community-driven, and consensus-built standard