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 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 A Política de Governança de Dados, Informação e Conhecimento da Embrapa como mecanismo para a gestão de dados de pesquisa agropecuários | Embrapa’s Data, Information and Knowledge Governance Policy as a framework for agricultural research data management

2019 ◽  
Vol 15 (2) ◽  
Author(s):  
Patrícia Rocha Bello Bertin ◽  
Juliana Meireles Fortaleza ◽  
Adriana Cristina Da Silva ◽  
Massayuki Franco Okawachi ◽  
Márcia De Oliveira Cardoso
Keyword(s):  
Big Data ◽  
Data Management ◽  
Agricultural Research ◽  
Original Data ◽  
Scientific Data ◽  
Research Data ◽  
Data Governance ◽  
Data Intensive ◽  
Scientific Data Management ◽  
Knowledge Policy

RESUMO O fenômeno Big Data e o quarto paradigma da ciência – a e-Science – demandam das instituições de ciência e tecnologia um apropriado gerenciamento e preservação dos dados de pesquisa, de modo a possibilitar o acesso, uso e compartilhamento dos dados originais e assim alcançar sustentabilidade e competitividade no sistema científico e tecnológico moderno. O presente trabalho comenta e analisa a Política de Governança de Dados, Informação e Conhecimento da Embrapa, com foco nas questões relacionadas à gestão de dados de pesquisa. Espera-se que essa Política possa ser instrumental para outras organizações do sistema de C&T nacional no desenvolvimento de seus próprios normativos.Palavras-chave: Dados Científicos; Ciência Intensiva em Dados; Acesso; Compartilhamento; Preservação; Gerenciamento.ABSTRACT The Big Data phenomenon and the fourth science paradigm - e-Science - demand from science and technology institutions proper management and preservation of research data, for access, use and sharing of original data and thus achieve sustainability. and competitiveness in the modern scientific and technological system. This paper comments and analyzes Embrapa’s Data Governance, Information and Knowledge Policy, focusing on issues related to scientific data management. It is hoped that this Policy can be instrumental to other organizations in the national S&T system in developing their own standards.Keywords: Scientific Data; Data Intensive Science; Access; Sharing; Preservation; Management.

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.

scholarly journals A conceptual framework for managing very diverse data for complex, interdisciplinary science

2011 ◽  
Vol 37 (6) ◽  
pp. 555-569 ◽  
Author(s):  
Mark A. Parsons ◽  
Øystein Godøy ◽  
Ellsworth LeDrew ◽  
Taco F. de Bruin ◽  
Bruno Danis ◽  
...  
Keyword(s):  
Critical Factor ◽  
Heterogeneous Data ◽  
Research Data ◽  
Library Science ◽  
Science Data ◽  
International Polar Year ◽  
Interdisciplinary Science ◽  
Data Intensive ◽  
Systemic Problems ◽  
Management Approaches

Much attention has been given to the challenges of handling massive data volumes in modern data-intensive science. This paper examines an equally daunting challenge – the diversity of interdisciplinary data, notably research data, and the need to interrelate these data to understand complex systemic problems such as environmental change and its impact. We use the experience of the International Polar Year 2007–8 (IPY) as a case study to examine data management approaches seeking to address issues around complex interdisciplinary science. We find that, while technology is a critical factor in addressing the interdisciplinary dimension of the data intensive science, the technologies developing for exa-scale data volumes differ from those that are needed for extremely distributed and heterogeneous data. Research data will continue to be highly heterogeneous and distributed and will require technologies to be much simpler and more flexible. More importantly, there is a need for both technical and cultural adaptation. We describe a vision of discoverable, open, linked, useful, and safe collections of data, organized and curated using the best principles and practices of information and library science. This vision provides a framework for our discussion and leads us to suggest several short- and long-term strategies to facilitate a socio-technical evolution in the overall science data ecosystem.

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).

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