AbstractThe main goal of this chapter is to share the technical details and best practices for setting up a scalable Big Data platform that addresses the data challenges of the food industry. The amount of data that is generated in our food supply chain is rapidly increasing. The data is published by hundreds of organizations on a daily basis, in many different languages and formats making its aggregation, processing, and exchange a challenge. The efficient linking and mining of the global food data can enable the generation of insights and predictions that can help food safety experts to make critical decisions. All the food companies as well as national authorities and agencies may highly benefit from the data services of such a data platform. The chapter focuses on the architecture and software stack that was used to set up a data platform for a specific business use case. We describe how the platform was designed following data and technology standards to ensure the interoperability between systems and the interconnection of data. We share best practices on the deployment of data platforms such as identification of records, orchestrating pipelines, automating the aggregation workflow, and monitoring of a Big Data platform. The platform was developed in the context of the H2020 BigDataGrapes project, was awarded by communities such as Elasticsearch, and is further developed in H2020 The Food Safety Market project in order to enable the setup of a data space for the food safety sector.

One of the significant challenges for the future is to guarantee safe food for all inhabitants of the planet. During the last 15 years, very important fraud issues like the '2013 horse meat scandal' and the '2008 Chinese milk scandal' have greatly affected the food industry and public health. One of the alternatives for this issue consists of increasing production, but to accomplish this, it is necessary that innovative options be applied to enhance the safety of the food supply chain. For this reason, it is quite important to have the right infrastructure in order to manage data of the food safety sector and provide useful analytics to Food Safety Experts. In this paper, we describe Agroknow's Big Data Platform architecture and examine its scalability for data management and experimentation.

It is evident that machine learning algorithms are being widely impacting industrial applications and platforms. Beyond typical research experimentation scenarios, there is a need for companies that wish to enhance their online data and analytics solutions to incorporate ways in which they can select, experiment, benchmark, parameterise and choose the version of a machine learning algorithm that seems to be most appropriate for their specific application context. In this paper, we describe such a need for a big data platform that supports food data analytics and intelligence. More specifically, we introduce Agroknow’s big data platform and identify the need to extend it with a flexible and interactive experimentation environment where different machine learning algorithms can be tested using a variation of synthetic and real data. A typical usage scenario is described, based on our need to experiment with various machine learning algorithms to support price prediction for food products and ingredients. The initial requirements for an experimentation environment are also introduced.

The enhancements in IT solutions and the open science movement are injecting changes in the practices dealing with data collection, collation, processing, analytics, and publishing in all the domains, including agri-food. However, in implementing these changes one of the major issues faced by the agri-food researchers is the fragmentation of the "assets" to be exploited when performing research tasks, for example, data of interest are heterogeneous and scattered across several repositories, the tools modelers rely on are diverse and often make use of limited computing capacity, the publishing practices are various and rarely aim at making available the "whole story" including datasets, processes, and results. This paper presents the AGINFRA PLUS endeavor to overcome these limitations by providing researchers in three designated communities with Virtual Research Environments facilitating the use of the "assets" of interest and promote collaboration.

Agricultural and food research are increasingly becoming fields where data acquisition, processing, and analytics play a major role in the provision and application of novelmethods in the general context of agri-food practices. The chapter focuses on the presentation of an innovative, holistic e-infrastructure solution that aims to enable researches for distinct but interconnected domains to share data, algorithms and results in a scalable and efficient fashion. It furthermore discusses on the potentially significant impact that such infrastructures can have on agriculture and food management and policy making, by applying the proposed solution in variegating agri-food related domains.

The purpose of this article is to study a broad set of journal papers related to metadata and quality in digital repositories and libraries, and to provide a quantitative analysis of the relevant research. It also aims at identifying open issues and future directions for research. A detailed search was carried out in relevant journals of information science, computer science, and library science; mainly, that allowed us to identify an extensive corpora of relevant work. The identified papers were classified based on an existing framework and a statistical analysis was carried out on the main classifications used within the framework. The analysis of the 702 papers identified, led to a series of statements for the field examined, focusing on the type of research carried out, the research methods deployed, and the research claims made. In addition, the papers were classified based on their target audiences, disciplines, as well as institutional and geographical origins. The article identifies areas in the literature that have not been addressed, as well as areas for future research. It also provides a clear image of the areas already researched, analyzing scientific literature that covers 20 years of repository/library deployment. This article makes an original contribution for researchers, practitioners, and managers of digital repositories and libraries alike as it provides a set of specific recommendations for the metadata and quality in digital repositories and libraries research agenda, along with a thorough analysis and classification of the research carried out so far.

Exposing eLearning objects on the Web of Data leads to sharing and reusing of educational resources and improves the interoperability of data on the Web. Furthermore, it enriches e-learning content, as it is connected to other valuable resources using the Linked Data principles. This paper describes a study performed on the Organic.Edunet repository, as an e-learning portal in an agricultural context. In this research, we experiment with exposing the Organic.Edunet metadata as Linked Open Data and interlinking its contents to several relevant datasets on the Web. An analysis of the metadata and of the interlinking results is presented in this paper as well.

In this paper, we explore how we may give researchers from different disciplines new tools to enrich and use the data that are made discoverable and accessible through Europeana, the digital cultural aggregator of Europe. This paper presents a use case where selected content from Europeana is used as a resource for Social Scientists working in the agriculture and food domain. The process starts with the profiling and the identification of content requirements of the research community of the Greek Agricultural Economics Research Institute (AGRERI) to the enrichment of its library with quality content from Europeana and the development of a discovery microsite for AGRERI, providing access to the aforementioned selected content. The paper presents the connection of this content with AGINFRA, the data infrastructure for European agricultural research. This paper aims to showcase how researchers working in completely different disciplines may discover and exploit data sets of interest to them, from the vast amount of resources available through Europeana. By using these resources, agricultural (and not only) researchers can investigate various topics using different scientific methods and tools, thus making multi-disciplinary agriculture research more useful and meaningful.

E-business processes are implemented through existing, as well as novel technologies. This book chapter focuses on the field of electronic markets (e-markets), and studies the technologies and solutions that are applied and proposed in this field. In particular, the chapter reviews e-market literature in order to identify which are the technological trends that have appeared in the e-markets field during the last decade. A conceptual model that allows for the classification of e-market research literature according to a number of technical topics is first introduced. Then, e-market literature is reviewed, and the technologies that seem to be attracting more research attention are identified. Representative contributions are discussed, and directions for future research are indicated. The overall aim of this chapter is to provide a blueprint of the literature related to e-business technologies for e-markets. IntroductIon According to the 2005 report of the United Nations Conference on Trade and Development (UNCTAD, 2005), e-commerce continues to grow in all sectors. In the United States (the largest e-commerce market), e-commerce is still most prominent in manufacturing and wholesale trade, but on the other hand, growth rates are highest in retail trade (B2C) and services. In the United States, the largest global e-commerce market, ecommerce sales have continuously grown during the last years. With a growth rate (24.7%) significantly higher than for total retail trade (4.3%), the share of e-commerce in total retail trade is also growing. The latest available figures indicate that its share has more than doubled (UNCTAD, 2005). Eurostat data (http://epp.eurostat.cec. eu.int/) show that for the European Union (EU), e-commerce sales over the Internet increased from 0.9% in 2002 to 2.2% in 2004. Compilations by E-Business Technologies in E-Market Literature the OECD suggest that online sales represent a small but growing share of total sales in most EU member countries, and that there is solid growth in B2C e-commerce (OECD, 2004). As a result, numerous electronic markets (emarkets) are continuously being deployed. For instance, the European Observatory of e-Markets eMarketServices (http://www.emarketservices. com) has listed, until January 2006, about 905 emarkets from various business sectors. E-markets aim to facilitate information exchange and support activities related to business process management and transactions. They are characterized by a frictionless and very low-cost flow of information between buyers and sellers. Moreover, they allow sellers to reach a wider consumer base, and buyers to have access to a large number of sellers. E-markets are therefore expected to create economic value for buyers, sellers, market intermediaries, and for society as a whole (Bakos, 1998; Grieger, 2003). In e-markets, proposed technologies and solutions vary from simple online catalogues that provide more information about products to interested customers, to sophisticated collaborative project management and supply-chain-management environments (Dai & Kauffman, 2002b). They address various technical topics, such as architectures, interoperability, services, protocols, data management, and networking. Nevertheless, there has not been, so far, a comprehensive overview of the technologies proposed, the dimensions addressed, or the solutions tested. This chapter aims to cover this aspect by providing a blueprint of research literature and e-business technologies for e-markets. An attempt to review and classify published research in this field can be an interesting and useful contribution to e-business researchers, managers, and practitioners/implementers. It can answer questions such as the following: which technical topics attract more attention in the field of e-markets? What are the proposed technologies and solutions? What are possible future directions of their development? Within this context, the aim of this chapter is to provide an overview of recent technological contributions in the field of e-markets. More specifically, it reports results from a study of e-market research that has been published during the past decade in scientific journals. The results provide interesting insight about the technologies for e-business processes in e-market environments, and outline implications for practice and research. The chapter is structured as follows. The “Background” section provides some background on e-markets, as well as an overview of relevant studies. “Methodology” presents the methodology followed in order to identify and classify e-market literature around technical topics. “Results” presents and discusses the results of the classification and reviews representative contributions. Finally, “Conclusion” provides the conclusions of this study and outlines some implications for related research.

E-business processes are implemented through existing, as well as novel technologies. This book chapter focuses on the field of electronic markets (e-markets), and studies the technologies and solutions that are applied and proposed in this field. In particular, the chapter reviews e-market literature in order to identify which are the technological trends that have appeared in the e-markets field during the last decade. A conceptual model that allows for the classification of e-market research literature according to a number of technical topics is first introduced. Then, e-market literature is reviewed, and the technologies that seem to be attracting more research attention are identified. Representative contributions are discussed, and directions for future research are indicated. The overall aim of this chapter is to provide a blueprint of the literature related to e-business technologies for e-markets. IGI PUBLISHING This paper appears in the publication, E-Business Process Management: Technologies and Solutions edited by J. Sounderpandan and T. Sinha © 2007, IGI Global 701 E. Chocolate Avenue, Suite 200, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.igi-pub.com ITB14091

Exposing eLearning objects on the Web of Data leads to sharing and reusing of educational resources and improves the interoperability of data on the Web. Furthermore, it enriches e-learning content, as it is connected to other valuable resources using the Linked Data principles. This paper describes a study performed on the Organic.Edunet repository, as an e-learning portal in an agricultural context. In this research, we experiment with exposing the Organic. Edunet metadata as Linked Open Data and interlinking its contents to several relevant datasets on the Web. An analysis of the metadata and of the interlinking results is presented in this paper as well. [ABSTRACT FROM AUTHOR]

This chapter presents an analysis of recommender systems in Technology-Enhanced Learning along their 15 years existence (2000–2014). All recommender systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender systems from 35 different countries have been investigated and categorised according to a given classification framework. The reviewed systems have been classified into seven clusters according to their characteristics and analysed for their contribution to the evolution of the RecSysTEL research field. Current challenges have been identified to lead the work of the forthcoming years.

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.

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.

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.