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Drakos A.,University of Alcalá | Protonotarios V.,University of Alcalá | Manouselis N.,Agro Know
F1000Research | Year: 2015

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. © 2015 Drakos A et al.


PubMed | Agro Know and University of Alcalá
Type: | Journal: F1000Research | Year: 2015

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.


Grant
Agency: European Commission | Branch: H2020 | Program: CSA | Phase: ICT-15-2014 | Award Amount: 4.98M | Year: 2015

BigDataEurope will provide support mechanisms for all the major aspects of a data value chain, in terms of the employed data and technology assets, the participating roles and the established or evolving processes. The effectiveness of the provided support mechanisms will be assessed in different domains pertaining to Europes major societal challenges with respect to the needs and requirements of the related communities. To this end, BigDataEurope focuses on providing an integrated stack of tools to manipulate, publish and use large-scale data resources; tools that can be installed and used freely in a customised data processing chain with minimal knowledge of the technologies involved and integrating and industrially hardening key open-source Big Data technologies and European research prototypes into a Big Data Integrator Platform, i.e. an ecosystem of specifications and reference implementations that are both attractive to current players from all parts of the data value chain while also lowering the entry barrier for new businesses. In order to realise its objectives, Big Data Europe will focus on two clearly defined coordination and support measures: 1. Coordination: Engaging with a diverse range of stakeholder groups representing particularly the Horizon 2020 societal challenges Health, Food & Agriculture, Energy, Transport, Climate, Social Sciences and Security; Collecting requirements for the ICT infrastructure needed by data-intensive science practitioners tackling a wide range of societal challenges; covering all aspects of publishing and consuming semantically interoperable, large-scale data and knowledge assets; 2. Support: Designing, realizing and evaluating a Big Data Aggregator platform infrastructure that meets requirements, minimises the disruption to current workflows, and maximises the opportunities to take advantage of the latest European RTD developments, including multilingual data harvesting, data analytics, and data visualisation. BigDataEurope will implement and apply two main instruments to successfully realize these coordination and support measures: a) Build Societal Big Data Interest Groups in the W3C interest group scheme and involving a large number of stakeholders from the Horizon 2020 societal challenges as well as technical Big Data experts; b) Design, integrate and deploy a cloud-deployment-ready Big Data aggregator platform comprising key open-source Big Data technologies for real-time and batch processing, such as Hadoop, Cassandra and Storm. BigDataEurope aims to provide an adaptable, easy to deploy and use solution, which will allow the interest-ed user groups and stakeholders to extend their Big Data solutions or introduce Big Data technology to their business processes, based on a concrete methodology for producing a technically sound solution and maximizing its outreach to the relevant communities.


Grant
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: ICT-10-2015 | Award Amount: 2.06M | Year: 2016

A major sustainability challenge for the European society is moving beyond conventional, industrialised food production and agricultural systems, characterised by a high use of external inputs. Mainstream conventional food production systems are posing a serious threat to the environment and to biodiversity and are becoming increasingly unsustainable due to unacceptable levels of food waste in industrialized countries and to shrinking farmers incomes. Alternative systems with reduced use of external inputs have to be promoted , based on i) an optimised use of agricultural biodiversity (hereafter agrobiodiversity), ecological processes and natural resources and on ii) improved food systems based e.g. on short supply chain quality food, where consumers play an active role in driving produce demand and consequently offer. CAPSELLA will address this challenge in two ways: (a) raising awareness on these issues especially within and among local communities (smallholders agriculture, biodiversity, food quality) but also within the broader European public, and (b) offering innovative ICT solutions that will address needs and requirements coming from the communities. To achieve this we will use a combination of participatory bottom up data collection and top down data integration to develop solutions for two domains: agrobiodiversity and local food knowledge. The project aims to (a) build from scratch open data repositories concerning regional agrobiodiversity, and (b) to build upon and enhance existing data sets on the agrobiodiversity and food domains. Based on these, the project will develop a number of community-driven data powered ICT solutions, which will be tested by the communities engaged in the project and will result in a number of pilots. Finally, our project will have a strong societal and business sustainability focus by also including incubation activities for selected pilots.


Manouselis N.,Agro Know | Karagiannidis C.,University of Thessaly | Sampson D.G.,University of Piraeus
Proceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014 | Year: 2014

This paper examines how a layered evaluation framework proposed for adaptive systems (AS) can be applied in the case of recommender systems (RecSys). Our analysis indicates that implementing a layered-based evaluation has the potential to facilitate a more detailed and informed evaluation of RecSys, allowing researchers and developers to better understand how to improve them. © 2014 IEEE.


Grant
Agency: European Commission | Branch: H2020 | Program: SME-1 | Phase: INSO-9-2015-1 | Award Amount: 71.43K | Year: 2015

The increase in food safety information quantity (e.g. through online sources) and diversity (e.g. information from social networks vs. structured surveillance programmes), results into a need to adequately discover and display information about food threats in a way that is customized to the users specific context and environment, in a highly usable and integrated format. Foodakai would like to take advantage of the identified business opportunity by harmonizing and making more user-friendly the discovery of information on foodborne diseases, food alerts, outbreaks and recalls. We aim to innovate the way information is discovered today, by combining and harmonizing food product recall and foodborne disease data from various, heterogeneous and dynamic online sources. We plan to apply text and data mining techniques, as well as forecasting and other analytical models, so that Foodakai provides tailored tracking, alerting and warning capabilities to its users. It will also be designed in a way that can allow users to adapt and customise the presented information so that it matches their preferences and information needs in a highly professional way - which contrasts this app from previous one-size-fits-all solutions.


Clements K.,University of Jyväskylä | Pawlowski J.,Ruhr West University of Applied Sciences | Manouselis N.,Agro Know
Computers in Human Behavior | Year: 2015

Today, Open Educational Resources (OER) are commonly stored, used, adapted, remixed and shared within Learning object repositories (LORs) which have recently started expanding their design to support collaborative teaching and learning. As numbers of OER available freely keep on growing, many LORs struggle to find sustainable business models and get the users' attention. Previous studies have shown that Quality assurance of the LORs is a significant factor when predicting the success of the repository. Within the study, we analysed technology enhanced learning literature systematically regarding LORs' quality approaches and specific collaborative instruments. This paper's theoretical contribution is a comprehensive framework of LOR quality approaches (LORQAF) that demonstrates the wide spectrum of possible approaches taken and classifies them. The purpose of this study is to assist LOR developers in designing sustainable quality assurance approaches utilizing full the potential of collaborative quality assurance tools. © 2015.


Koutoumanos A.,Computer Technology Institute and Press Diophantus | Protonotarios V.,Agro Know | Drakos A.,Agro Know | Toader M.,University of Bucharest
Agris On-line Papers in Economics and Informatics | Year: 2014

The agricultural education covers all levels of formal education but focuses mostly on the higher ones as well as the vocational education and training. Online courses play an important role in the educational context and compared to traditional courses they eliminate the location and time restrictions and allow a self-paced attendance of a curriculum. At the same time, the existence of online courses raised the need for the design and implementation of the appropriate platforms which may be used for the organization and deployment of online courses. This paper presents the case of agriMoodle, a course management platform based on the widely used Moodle platform, which provides a number of enhancements in the form of modules or widgets specialized for the agricultural domain. These modules aim to enhance the user experience and the functionalities of a standard Moodle installation.


Celli F.,Food and Agriculture Organization of the United Nations | Malapela T.,Food and Agriculture Organization of the United Nations | Wegner K.,Food and Agriculture Organization of the United Nations | Subirats I.,Food and Agriculture Organization of the United Nations | And 2 more authors.
F1000Research | Year: 2015

AGRIS is the International System for Agricultural Science and Technology. It is supported by a large community of data providers, partners and users. AGRIS is a database that aggregates bibliographic data, and through this core data, related content across online information systems is retrieved by taking advantage of Semantic Web capabilities. AGRIS is a global public good and its vision is to be a responsive service to its user needs by facilitating contributions and feedback regarding the AGRIS core knowledgebase, AGRIS's future and its continuous development. Periodic AGRIS e-consultations, partner meetings and user feedback are assimilated to the development of the AGRIS application and content coverage. This paper outlines the current AGRIS technical set-up, its network of partners, data providers and users as well as how AGRIS's responsiveness to clients' needs inspires the continuous technical development of the application. The paper concludes by providing a use case of how the AGRIS stakeholder input and the subsequent AGRIS e-consultation results influence the development of the AGRIS application, knowledgebase and service delivery. © 2015 Celli F et al.


PubMed | Food and Agriculture Organization of the United Nations and Agro Know
Type: | Journal: F1000Research | Year: 2015

AGRIS is the International System for Agricultural Science and Technology. It is supported by a large community of data providers, partners and users. AGRIS is a database that aggregates bibliographic data, and through this core data, related content across online information systems is retrieved by taking advantage of Semantic Web capabilities. AGRIS is a global public good and its vision is to be a responsive service to its user needs by facilitating contributions and feedback regarding the AGRIS core knowledgebase, AGRISs future and its continuous development. Periodic AGRIS e-consultations, partner meetings and user feedback are assimilated to the development of the AGRIS application and content coverage. This paper outlines the current AGRIS technical set-up, its network of partners, data providers and users as well as how AGRISs responsiveness to clients needs inspires the continuous technical development of the application. The paper concludes by providing a use case of how the AGRIS stakeholder input and the subsequent AGRIS e-consultation results influence the development of the AGRIS application, knowledgebase and service delivery.

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