publications

Agile retrieval of Big Data with EarthServe

With the unprecedented increase of orbital sensor, in-situ measurement, and simulation data there is a rich, yet not leveraged potential for getting insights from dissecting datasets and rejoining them with other datasets. Obviously, the goal is to allow users to "ask any question, any time" thereby enabling them to "build their own product on the go".

The rasdaman Open-Source Array DBMS.

Rasdaman ("raster data manager") has pioneered Array Databases by adding massive multi-dimensional gridded data, an information category long missing in databases, to scalable data management and analysis. Its declarative query language, rasql, extends SQL with array operators which are optimized and parallelized on server side. Installations can easily be mashed up securely, thereby enabling largescale location-transparent query processing in federations. Domain experts value the integration with their commonly used tools leading to a quick learning curve.

Big Earth Data at Your Fingertips

The term "Big Data" is a contemporary shorthand characterizing data which are too large, fast-lived, heterogeneous, or complex to get understood and exploited. Technologically, this is a cross-cutting challenge affecting both storage and processing, data and metadata, servers and clients as well as mashups. Further, making new, substantially more powerful tools available for simple use by non-experts while not constraining complex tasks of experts just adds to the complexity. All this holds for many application domains, but specifically so for the field of Earth Observation (EO).

EarthServer: Big Earth Datacubes at Your Fingertips

"Big Data" is a shorthand for data too large, fast-lived, heterogeneous, or complex to get understood and exploited. Technologically, this affects storage and processing, data and metadata, servers and clients as well as mashups. Further, more powerful tools must be available for simple regular use while not constraining experts. Challenge is to allow users to "ask any question, any time" enabling them to "build their own product".

Achieving Interoperability with Big Geo Data Standards

With OGC coverages, a concrete, interoperable data model has been established which unifies n-D spatio-temporal regular and irregular grids, point clouds, and meshes - hence, the main contributors to today's Big Geo Data. While coverages can be served through many OGC services, the Web Coverage Service (WCS) suite provides versatile streamlined coverage functionality ranging from simple access to flexible spatio-temporal analytics. Flexibility and scalability of the WCS suite has been demonstrated in practice through services with up to 130+ TB of space/time datacubes.

WCS for INSPIRE: Analyzing Massive Spatio-Temporal Datacubes.

The transatlantic EarthServer initiative has made spatio-temporal analytics a commodity for scientists,
engineers, and decision makers.

By utilizing novel parallel Array Database technology with frontends strictly based on the open OGC
standards, datacubes have become first-class citizens accessible through direct interaction with simple
point-and-click Web GUIs Flexibility and scalability of this approach has shown on 130+ TB datasets
together covering Earth and Planetary sciences.

Asterix and Obelix: How Standards Reunite Data and Metadata

There is a traditional saying that metadata are understandable, semantic-rich, and searchable whereas data are big, with no accessible semantics, and just downloadable – a little bit like smart little Asterix and fat, unintelligent Obelix in the well-known comics. Not only has this led to an imbalance of search support from a user perspective, but also underneath to a deep technology divide often using relational databases for metadata and bespoke archive solutions for data.

EO Data Service:an efficient datacube structure coupled with the virtual globe technology

The EO Open Science 2016 conference was held at ESA’s ESRIN centre in Frascati, Italy, on 12–14 September 2016. The conference aimed to explore new challenges and opportunities for satellite Earth observation research created by the rapid advances in information and communications technologies.

Enabling Technology for Exploitation of Earth Observation Products in the Big Data Era

TORUS is a project funded by the European Union in the framework of Erasmus+ Capacity Building. This program funds “transnational partnerships between educational institutions and organizations, training and youth programs in order, promoting cooperation and development”.

EO Data Service: Enabling Technology for Exploitation of Earth Observation Products in the Big Data Era

The use of Earth Observation (EO) data is becoming more and more challenging as a consequence of the volume and variety of data and the needs of the users that exploit the data.

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