Lorenzo Bigagli

Big Data Analytics for Earth Sciences: the EarthServer approach

Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and simulations. However, Earth Science data and applications present specificities in terms of relevance of the geospatial information, wide heterogeneity of data models and formats, and complexity of processing. Therefore, Big Earth Data Analytics requires specifically tailored techniques and tools. The EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets, built around a high performance array database technology, and the adoption and enhancement of standards for service interaction (OGC WCS and WCPS). The EarthServer solution, led by the collection of requirements from scientific communities and international initiatives, provides a holistic approach that ranges from query languages and scalability up to mobile access and visualization. The result is demonstrated and validated through the development of lighthouse applications in the Marine, Geology, Atmospheric, Planetary and Cryospheric science domains.

Discovery, Mediation, and Access Services for Earth Observation Data

The international research community involved in the GMES, INSPIRE, and GEOSS initiatives is actively pursuing the specification of information and service oriented solutions for geospatial data interoperability. A prominent interoperability issue pertains to discovery services. From an information technology point of view, the challenge is to implement interoperable discovery services for data and processing resources that are collected and managed using multidisciplinary standards and tools. We have designed and experimented a new, improved model and technology for the discovery of geospatial resources: an advanced catalog service featuring additional functionalities like mediation and asynchronous distribution. Besides, the described solution addresses another well-recognized issue: the integration of discovery and access services for complex resources-such as EO datasets.

Transport infrastructure surveillance and monitoring by electromagnetic sensing: the ISTIMES project

The ISTIMES project, funded by the European Commission in the frame of a joint Call “ICT and Security” of the Seventh Framework Programme, is presented and preliminary research results are discussed. The main objective of the ISTIMES project is to design, assess and promote an Information and Communication Technologies (ICT)-based system, exploiting distributed and local sensors, for non-destructive electromagnetic monitoring of critical transport infrastructures. The integration of electromagnetic technologies with new ICT information and telecommunications systems enables remotely controlled monitoring and surveillance and real time data imaging of the critical transport infrastructures. The project exploits different non-invasive imaging technologies based on electromagnetic sensing (optic fiber sensors, Synthetic Aperture Radar satellite platform based, hyperspectral spectroscopy, Infrared thermography, Ground Penetrating Radar-, low-frequency geophysical techniques, Ground based systems for displacement monitoring). In this paper, we show the preliminary results arising from the GPR and infrared thermographic measurements carried out on the Musmeci bridge in Potenza, located in a highly seismic area of the Apennine chain (Southern Italy) and representing one of the test beds of the project.

Unidata’s Common Data Model mapping to the ISO 19123 Data Model

Access to real-time distributed Earth and Space Science (ESS) information is essential for enabling critical Decision Support Systems (DSS). Thus, data model interoperability between the ESS and DSS communities is a decisive achievement for enabling cyber-infrastructure which aims to serve important societal benefit areas. The ESS community is characterized by a certain heterogeneity, as far as data models are concerned. Recent spatial data infrastructures implement international standards for the data model in order to achieve interoperability and extensibility. This paper presents well-accepted ESS data models, introducing a unified data model called the Common Data Model (CDM). CDM mapping into the corresponding elements of the international standard coverage data model of ISO 19123 is presented and discussed at the abstract level. The mapping of CDM scientific data types to the ISO coverage model is a first step toward interoperability of data systems. This mapping will provide the abstract framework that can be used to unify subsequent efforts to define appropriate conventions along with explicit agreed-upon encoding forms for each data type. As a valuable case in point, the content mapping rules for CDM grid data are discussed addressing a significant example.

GI-Cat: a Web service for dataset cataloguing based on ISO 19115

We present the GI-Cat service: a SOAP-based Web service providing basic functionalities for GI dataset cataloguing and access. The GJ-Cat object model schema is instance of the hierarchical, semistructured data model and is based on the ISO 19115 data model. GI-Cat requirements, information model (resources and accompanying metadata) and functional modules are introduced. Some of the architectural and technological aspects of an experimental implementation of the service are briefly described. Eventually, we relate GI-Cat to OWS/spl trade/ specifications. The proposed solution is being currently experimented in the framework of the COS(OT) project, that is part of the Italian National Operating Program on Scientific and Technological Research and High Education.

GALEON: Standards-based Web Services for Interoperability among Earth Sciences Data Systems

One barrier to research at the boundaries of the traditional Earth sciences is a lack of interoperability among data systems employed in the traditional subdisciplines. Solid Earth scientists (including the hydrology community) have tended to view their datasets as descriptions of discrete objects with attributes that can be stored and manipulated conveniently in a database. Geographic Information Systems (GIS) work well in this environment. On the other hand, the oceanographic and atmospheric sciences (the Fluid Earth Sciences or FES) communities think of data as discrete points in a continuous mathematical function space where the behavior of multiple parameters in space and time is governed by a set of equations.

Bringing GEOSS Services into Practice: A Capacity Building Resource on Spatial Data Infrastructures (SDI)

Data discoverability, accessibility, and integration are frequent barriers for scientists and a major obstacle for favorable results on environmental research. To tackle this issue, the Group on Earth Observations (GEO) is leading the development of the Global Earth Observation System of Systems (GEOSS), a voluntary effort that connects Earth Observation resources world-wide, acting as a gateway between producers and users of environmental data. GEO recognizes the importance of capacity building and education to reach large adoption, acceptance and commitment on data sharing principles to increase the capacity to access and use Earth Observations data. This article presents “Bringing GEOSS services into practice” (BGSIP), an integrated set of teaching material and software to facilitate the publication and use of environmental data through standardized discovery, view, download, and processing services, further facilitating the registration of data into GEOSS. So far, 520 participants in 10 countries have been trained using this material, leading to numerous Spatial Data Infrastructure implementations and 1,000 tutorial downloads. This workshop lowers the entry barriers for both data providers and users, facilitates the development of technical skills, and empowers people.

Discovery, query and access services for imagery, gridded and coverage data a clearinghouse solution

The development of catalog clearinghouse solutions is a near-term challenge in support of fully functional and useful infrastructures for spatial data. We present an experimental catalog clearinghouse for Imagery, gridded and coverage data. The solution supports data discovery, evaluation, query distribution and mediation of several well-known catalog systems.

The new OGC Publish/Subscribe Standard - applications in the Sensor Web and the Aviation domain

The Open Geospatial Consortium (OGC) has conducted much work in the past on event-based models and architectures. However, the current OGC standard baseline only supports synchronous web service capabilities, which have insofar primarily addressed the request/reply model, where a client makes a request and the server usually responds synchronously, with either the requested information or a failure. Recently, the OGC Publish/Subscribe 1.0 Standard has introduced an abstract model for publish/subscribe message exchange, a long-awaited building block in the OGC suite of geospatial standards. The publish/subscribe pattern is distinguished from the request/reply one by the asynchronous delivery of messages and the ability for a client to specify an ongoing, persistent expression of interest. In this work, we report on the experimentation of the new OGC Publish/Subscribe 1.0 Standard in the context of the OGC Testbed-12 initiative and related fields of work, particularly in the application domains of Sensor Web and Aviation. We illustrate and discuss the enhancements in comparison to previous OGC service architectures, highlighting the benefits of introducing the PubSub 1.0 Standard into the considered systems and their workflows.

Applying SOA to earth observation: the COS(OT) experience

In this work, we introduce an implementation of COS(OT), an open federated framework allowing discovery and interoperability of disparate geographic information resources and it also implements some concept of an SDI for environmental sciences datasets. Environmental sciences data is a kind of geoinformation dealing with phenomena implicitly and explicitly associated with a location relative to the Earth. In the context of COS(OT), the managed data is of imagery, gridded and coverage data (IGCD) stemming from Earth observation. On the other hand, the service-oriented approach which has semistructured data model and latest standard Web technologies with the current geomatics standardization process and it is used to prove as a feasible solution to the problem. Thus the two main COS(OT) business processes are described an their implementations are reported.