Shared metadata for data-centric materials science
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We present SexTant, a Web-based system for the visualization and exploration of time-evolving linked geospatial data and the creation, sharing, and collaborative editing of "temporally-enriched" thematic maps which are produced by combining different sourc ...
The ability of smart meters to communicate energy consumption data in (near) real-time enables data analytics for novel applications, such as pervasive demand response, personalized energy feedback, outage management, and theft detection. Smart meter data ...
This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of related mobile data analysis methodologies. Fir ...
The field of neuroscience is witnessing a huge influx of experimental data thanks to the improvements in the data acquisition tools and techniques. Most of this data is being collected by thousands of experimenters located in various institutions around th ...
Thanks to recent technology related to product monitoring and data communication, it is now possible for a company to gather various kinds of product usage data during its operation in a ubiquitous way. However, the application of the newly gathered data i ...
Background: New experimental methods must be developed to study interaction networks in systems biology. To reduce biological noise, individual subjects, such as single cells, should be analyzed using high throughput approaches. The measurement of several ...
Mobile, social, real-time: the ongoing revolution in the way people communicate has given rise to a new kind of epidemiology. Digital data sources, when harnessed appropriately, can provide local and timely information about disease and health dynamics in ...
Open data initiatives are characterized, in several countries, by a great extension of the number of data sets made available for access by public administrations, constituencies, businesses and other actors, such as journalists, international institutions ...
As the Sensor Internet starts to become reality, increasingly heterogeneous sensor networks are becoming interconnected into federated sensor networks and provide huge volumes of sensor data for a variety of applications to large user communities, such as ...
Machine learning is a broad discipline that comprises a variety of techniques for extracting meaningful information and patterns from data. It draws on knowledge and "know-how" from various scientific areas such as statistics, graph theory, linear algebra, ...
