A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

RAPID WEBGIS DEVELOPMENT FOR EMERGENCY MANAGEMENT

The use of spatial data during emergency response and management helps to make faster and better decisions. Moreover spatial data should be as much updated as possible and easy to access. To face the challenge of rapid and updated data sharing the most efficient solution is largely considered the use of internet where the field of web mapping is constantly evolving. ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action) is a non profit association founded by Politecnico di Torino and SITI (Higher Institute for the Environmental Systems) as a joint project with the WFP (World Food Programme). The collaboration with the WFP drives some projects related to Early Warning Systems (i.e. flood and drought monitoring) and Early Impact Systems (e.g. rapid mapping and assessment through remote sensing systems). The Web GIS team has built and is continuously improving a complex architecture based entirely on Open Source tools. This architecture is composed by three main areas: the database environment, the server side logic and the client side logic. Each of them is implemented respecting the MCV (Model Controller View) pattern which means the separation of the different logic layers (database interaction, business logic and presentation). The MCV architecture allows to easily and fast build a Web GIS application for data viewing and exploration. In case of emergency data publication can be performed almost immediately as soon as data production is completed. The server side system is based on Python language and Django web development framework, while the client side on OpenLayers, GeoExt and Ext.js that manage data retrieval and user interface. The MCV pattern applied to javascript allows to keep the interface generation and data retrieval logic separated from the general application configuration, thus the server side environment can take care of the generation of the configuration file. The web application building process is data driven and can be considered as a view of the current architecture composed by data and data interaction tools. Once completely automated, the Web GIS application building process can be performed directly by the final user, that can customize data layers and controls to interact with the

Spatial Aided Decision-making System for E-Government

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Data integration in a modular and parallel grid-computing workflow

In the past decades a wide range of complex processes have been developed to solve specific geospatial data integration problems. As a drawback these complex processes are often not sufficiently transferable and interoperable. We propose modularisation of the whole data integration process into reusable, exchangeable, and multi-purpose web services to overcome these drawbacks. Both a high-level split of the process into subsequent modules such as pre-processing and feature matching is discussed as well as another fine-granular split within these modules. Thereby complex integration problems can be addressed by chaining selected services as part of a geo-processing workflow. Parallelization is needed for processing massive amounts of data or complex algorithms. In this paper the two concepts of task and data parallelization are compared and examples for their usage are given. The presented work provides vector data integration within grid-computing workflows of the German Spatial Data Infrastructure Grid (SDI-Grid) project.BMB

From Social Data Mining to Forecasting Socio-Economic Crisis

Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio