scholarly journals agINFRA: a research data hub for agriculture, food and the environment

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 127
Author(s):  
Andreas Drakos ◽  
Vassilis Protonotarios ◽  
Nikos Manouselis
Keyword(s):  
Agricultural Research ◽  
Heterogeneous Data ◽  
Multiple Roles ◽  
Scientific Communities ◽  
Data Intensive ◽  
Domain Specific ◽  
Food Research ◽  
Heterogeneous Data Sources ◽  
Funded Project ◽  
Research And Education

The agINFRA project (www.aginfra.eu) was a European Commission funded project under the 7th Framework Programme that aimed to introduce agricultural scientific communities to the vision of open and participatory data-intensive science. agINFRA has now evolved into the European hub for data-powered research on agriculture, food and the environment, serving the research community through multiple roles.Working on enhancing the interoperability between heterogeneous data sources, the agINFRA project has left a set of grid- and cloud- based services that can be reused by future initiatives and adopted by existing ones, in order to facilitate the dissemination of agricultural research, educational and other types of data. On top of that, agINFRA provided a set of domain-specific recommendations for the publication of agri-food research outcomes. This paper discusses the concept of the agINFRA project and presents its major outcomes, as adopted by existing initiatives activated in the context of agricultural research and education.

scholarly journals agINFRA: a research data hub for agriculture, food and the environment

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 127 ◽  
Author(s):  
Andreas Drakos ◽  
Vassilis Protonotarios ◽  
Nikos Manouselis
Keyword(s):  
Agricultural Research ◽  
Heterogeneous Data ◽  
Research Data ◽  
Scientific Communities ◽  
Data Intensive ◽  
Domain Specific ◽  
Food Research ◽  
Heterogeneous Data Sources ◽  
Funded Project ◽  
Research And Education

The agINFRA project (www.aginfra.eu) is a European Commission funded project under the 7th Framework Programme that aimed to introduce agricultural scientific communities to the vision of open and participatory data-intensive science. Working on enhancing the interoperability between heterogeneous data sources, the agINFRA project has left a set of grid- and cloud- based services that can be reused by future initiatives and adopted by existing ones, in order to facilitate the dissemination of agricultural research, educational and other types of data. On top of that, agINFRA provided a set of domain-specific recommendations for the publication of agri-food research outcomes. This paper discusses the concept of the agINFRA project and presents its major outcomes, as adopted by existing initiatives activated in the context of agricultural research and education.

scholarly journals CDI/THREDDS interoperability in the SeaDataNet framework

2010 ◽  
Vol 28 ◽  
pp. 17-27 ◽  
Author(s):  
S. Nativi ◽  
P. Mazzetti ◽  
M. Santoro ◽  
E. Boldrini ◽  
G. M. R. Manzella ◽  
...  
Keyword(s):  
Biological Properties ◽  
Heterogeneous Data ◽  
International Standards ◽  
Information Discovery ◽  
Geospatial Information ◽  
Data Infrastructure ◽  
Metadata Model ◽  
Heterogeneous Data Sources ◽  
Discovery Service ◽  
Funded Project

Abstract. SeaDataNet is an EU funded project aiming to create and operate a pan-European, marine data infrastructure for managing the large and diverse datasets (i.e. temperature, salinity current, sea level, chemical, physical and biological properties) collected by the oceanographic fleets and the new automatic observation systems. In order to make the SeaDataNet system compliant with the INSPIRE Implementing Rules for discovery service, an ISO 19139 encoding of the SeaDataNet Common Data Index (CDI) metadata model was defined. Moreover, the problem of heterogeneous data sources has been addressed. In fact, a widely used system of SeaDataNet partners and oceanographic-marine community is THREDDS/OPeNDAP; this raises up the problem of federating into SeaDataNet framework THREDDS/OPeNDAP systems as well. In this paper we describe an interoperability framework to access resources (i.e. data and services) that are available through CDI and THREDDS/OPeNDAP services. The proposed solution implements a common catalog interface to discover and access the two heterogeneous resources in a common way. This catalog service is fully distributed and implements international standards as far as geospatial information discovery and query are concerned. The developed solution is called GI-cat and was experimented in the framework of the SeaDataNet European project.

TECHNIQUES FOR OPTIMIZATION OF QUERIES ON INTEGRATED BIOLOGICAL RESOURCES

2004 ◽  
Vol 02 (02) ◽  
pp. 375-411 ◽  
Author(s):  
ZOÉ LACROIX ◽  
LOUIQA RASCHID ◽  
BARBARA A. ECKMAN
Keyword(s):  
Scientific Discovery ◽  
Heterogeneous Data ◽  
Semantic Knowledge ◽  
Scientific Data ◽  
Integration Platform ◽  
Domain Specific ◽  
Heterogeneous Data Sources ◽  
Support Tools ◽  
Efficient Integration ◽  
Scientific Integration

Today, scientific data are inevitably digitized, stored in a wide variety of formats, and are accessible over the Internet. Scientific discovery increasingly involves accessing multiple heterogeneous data sources, integrating the results of complex queries, and applying further analysis and visualization applications in order to collect datasets of interest. Building a scientific integration platform to support these critical tasks requires accessing and manipulating data extracted from flat files or databases, documents retrieved from the Web, as well as data that are locally materialized in warehouses or generated by software. The lack of efficiency of existing approaches can significantly affect the process with lengthy delays while accessing critical resources or with the failure of the system to report any results. Some queries take so much time to be answered that their results are returned via email, making their integration with other results a tedious task. This paper presents several issues that need to be addressed to provide seamless and efficient integration of biomolecular data. Identified challenges include: capturing and representing various domain specific computational capabilities supported by a source including sequence or text search engines and traditional query processing; developing a methodology to acquire and represent semantic knowledge and metadata about source contents, overlap in source contents, and access costs; developing cost and semantics based decision support tools to select sources and capabilities, and to generate efficient query evaluation plans.

scholarly journals Accessible Routes Integrating Data from Multiple Sources

2020 ◽  
Vol 10 (1) ◽  
pp. 7
Author(s):  
Miguel R. Luaces ◽  
Jesús A. Fisteus ◽  
Luis Sánchez-Fernández ◽  
Mario Munoz-Organero ◽  
Jesús Balado ◽  
...  
Keyword(s):  
Information System ◽  
Data Model ◽  
Large Scale ◽  
Heterogeneous Data ◽  
Multiple Sources ◽  
Heterogeneous Data Sources ◽  
Different Types ◽  
Software Sensors ◽  
The City

Providing citizens with the ability to move around in an accessible way is a requirement for all cities today. However, modeling city infrastructures so that accessible routes can be computed is a challenge because it involves collecting information from multiple, large-scale and heterogeneous data sources. In this paper, we propose and validate the architecture of an information system that creates an accessibility data model for cities by ingesting data from different types of sources and provides an application that can be used by people with different abilities to compute accessible routes. The article describes the processes that allow building a network of pedestrian infrastructures from the OpenStreetMap information (i.e., sidewalks and pedestrian crossings), improving the network with information extracted obtained from mobile-sensed LiDAR data (i.e., ramps, steps, and pedestrian crossings), detecting obstacles using volunteered information collected from the hardware sensors of the mobile devices of the citizens (i.e., ramps and steps), and detecting accessibility problems with software sensors in social networks (i.e., Twitter). The information system is validated through its application in a case study in the city of Vigo (Spain).

scholarly journals Improving Sustainability of Smart Cities through Visualization Techniques for Big Data from IoT Devices

2020 ◽  
Vol 12 (14) ◽  
pp. 5595 ◽  
Author(s):  
Ana Lavalle ◽  
Miguel A. Teruel ◽  
Alejandro Maté ◽  
Juan Trujillo
Keyword(s):  
Big Data ◽  
Smart City ◽  
Smart Cities ◽  
Fire Department ◽  
Heterogeneous Data ◽  
Fire Extinguishing ◽  
Heterogeneous Data Sources ◽  
Iot Devices ◽  
Visualization Techniques ◽  
The Impact

Fostering sustainability is paramount for Smart Cities development. Lately, Smart Cities are benefiting from the rising of Big Data coming from IoT devices, leading to improvements on monitoring and prevention. However, monitoring and prevention processes require visualization techniques as a key component. Indeed, in order to prevent possible hazards (such as fires, leaks, etc.) and optimize their resources, Smart Cities require adequate visualizations that provide insights to decision makers. Nevertheless, visualization of Big Data has always been a challenging issue, especially when such data are originated in real-time. This problem becomes even bigger in Smart City environments since we have to deal with many different groups of users and multiple heterogeneous data sources. Without a proper visualization methodology, complex dashboards including data from different nature are difficult to understand. In order to tackle this issue, we propose a methodology based on visualization techniques for Big Data, aimed at improving the evidence-gathering process by assisting users in the decision making in the context of Smart Cities. Moreover, in order to assess the impact of our proposal, a case study based on service calls for a fire department is presented. In this sense, our findings will be applied to data coming from citizen calls. Thus, the results of this work will contribute to the optimization of resources, namely fire extinguishing battalions, helping to improve their effectiveness and, as a result, the sustainability of a Smart City, operating better with less resources. Finally, in order to evaluate the impact of our proposal, we have performed an experiment, with non-expert users in data visualization.

scholarly journals biotoolsSchema: a formalized schema for bioinformatics software description

GigaScience ◽  
2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jon Ison ◽  
Hans Ienasescu ◽  
Emil Rydza ◽  
Piotr Chmura ◽  
Kristoffer Rapacki ◽  
...  
Keyword(s):  
Scientific Community ◽  
Life Science ◽  
Technical Information ◽  
Heterogeneous Data ◽  
Digital Resources ◽  
Data Intensive ◽  
Research Software ◽  
Bioinformatics Software ◽  
Scientific Context ◽  
Machine Readable

Abstract Background Life scientists routinely face massive and heterogeneous data analysis tasks and must find and access the most suitable databases or software in a jungle of web-accessible resources. The diversity of information used to describe life-scientific digital resources presents an obstacle to their utilization. Although several standardization efforts are emerging, no information schema has been sufficiently detailed to enable uniform semantic and syntactic description—and cataloguing—of bioinformatics resources. Findings Here we describe biotoolsSchema, a formalized information model that balances the needs of conciseness for rapid adoption against the provision of rich technical information and scientific context. biotoolsSchema results from a series of community-driven workshops and is deployed in the bio.tools registry, providing the scientific community with >17,000 machine-readable and human-understandable descriptions of software and other digital life-science resources. We compare our approach to related initiatives and provide alignments to foster interoperability and reusability. Conclusions biotoolsSchema supports the formalized, rigorous, and consistent specification of the syntax and semantics of bioinformatics resources, and enables cataloguing efforts such as bio.tools that help scientists to find, comprehend, and compare resources. The use of biotoolsSchema in bio.tools promotes the FAIRness of research software, a key element of open and reproducible developments for data-intensive sciences.

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