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The enhancements in IT solutions and the open science movement are injecting changes in the practices dealing with data collection, collation, processing and 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, e.g. data of interest are heterogeneous and scattered across several repositories, the tools modellers 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” with datasets, processes, workflows. This paper presents the AGINFRA PLUS endeavour 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.

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. © 2020 John Wiley & Sons Ltd

Errors have occurred during the production process. On page 15, Sect. 7, third paragraph, tenth line, the sentence should read: “The number of data points in the HCV light curves ranges from five (our cut-olimit) to 120.” And the citation “Spetsieri et al. 2019” should be “Spetsieri et al., in prep.”, in the first paragraph of Sect. 7.4 (page 19), and in Sect. 8, second to last paragraph (page 21). © 2019 EDP Sciences. All rights reserved.

Deliverable D10.2 - "BlueBRIDGE Resources Federation Facilities: Revised Version" reports the release of the BlueBRIDGE facilities for integration of resources from external infrastructures and management of integrated resources. It is structured as follows: a description for each facility is available on this document in conjunction witha list of the main features, information about the design and architecture of it, a number of use cases and finally how it can be deployed. In case more information is needed or a more detailed documentation is available, URLs to the project 's wiki are provided. The set of the available facilities are split in three main categories: (a) facilities for integrating computing infrastructure resources, aiming on exploiting the computational power offered by external infrastructures in order to execute CPU intensive jobs, (b) facilities for integrating data infrastructure resources, where a number of components have been developed in order to integrate data from different data infrastructures to in the Virtual Research Environments (VREs), including biodiversity, geospatial and generic OAI-PMH repositories and (c) facilities for federated resources management, for effectively and efficiently managing the federated resources made available thanks to bridges developed in the previous categories. The sections that follow provide the description and the details for each distinct facility, aiming on offering a complete guide to the intended readers. The intended readers of this deliverable are (a) the community in the large willing to be informed on the solutions BlueBRIDGE offers for federated resources management, (b) the gCube developer community to know how to integrate, use and build on top of the facilities described by the document, and (c) the gCube administrators to know how to setup, configure and manage the integration of a gCube infrastructure with external resources.

Agri-food research calls for changes in the practices dealing with data collection, collation, processing and analytics, and publishing thus to fully benefit from and contribute to the Open Science movement. One of the major issues faced by the agri-food researchers is the fragmentation of the “assets” that can be exploited when performing research tasks, e.g. data of interest are heterogeneous and scattered across several repositories, the tools exploited by modellers are diverse and often rely on local computing environments, the publishing practices are various and rarely aim at making available the “whole story” with datasets, processes, workflows. This paper presents the AGINFRA+endeavour to overcome these limitations by providing researchers in three designated communities with Virtual Research Environments facilitating the access to and use of the “assets” of interest and promote collaboration.

The Hubble Source Catalog (HSC) combines lists of sources detected on images obtained with the WFPC2, ACS and WFC3 instruments aboard the Hubble Space Telescope (HST) and now available in the Hubble Legacy Archive. The catalogue contains time-domain information for about two million of its sources detected using the same instrument and filter on at least five HST visits. The Hubble Catalog of Variables (HCV) aims to identify HSC sources showing significant brightness variations. A magnitude-dependent threshold in the median absolute deviation of photometric measurements (an outlier-resistant measure of light-curve scatter) is adopted as the variability detection statistic. It is supplemented with a cut in χred2 that removes sources with large photometric errors. A pre-processing procedure involving bad image identification, outlier rejection and computation of local magnitude zero-point corrections is applied to the HSC light-curves before computing the variability detection statistics. About 52 000 HSC sources have been identified as candidate variables, among which 7,800 show variability in more than one filter. Visual inspection suggests that ∼70% of the candidates detected in multiple filters are true variables, while the remaining ∼30% are sources with aperture photometry corrupted by blending, imaging artefacts or image processing anomalies. The candidate variables have AB magnitudes in the range 15-27m, with a median of 22m. Among them are the stars in our own and nearby galaxies, and active galactic nuclei. © International Astronomical Union 2019.

We aim to construct an exceptionally deep (V less than or similar to 27) catalog of variable objects in selected Galactic and extragalactic fields visited multiple times by the Hubble Space Telescope (HST). While HST observations of some of these fields were searched for specific types of variables before ( most notably, the extragalactic Cepheids), we attempt a systematic study of the population of variable objects of all types at the magnitude range not easily accessible with ground-based telescopes. The variability timescales that can be probed range from hours to years depending on how often a particular field has been visited. For source extraction and cross-matching of sources between visits we rely on the Hubble Source Catalog which includes 107 objects detected with WFPC2, ACS, and WFC3 HST instruments. The lightcurves extracted from the HSC are corrected for systematic effects by applying local zero-point corrections and are screened for bad measurements. For each lightcurve we compute variability indices sensitive to a broad range of variability types. The indices characterize the overall lightcurve scatter and smoothness. Candidate variables are selected as having variability index values significantly higher than expected for objects of similar brightness in the given set of observations. The Hubble Catalog of Variables will be released in 2018.

The Hubble Catalog of Variables (HCV) is a 3 year ESA funded project that aims to develop a set of algorithms to identify variables among the sources included in the Hubble Source Catalog (HSC) and produce the HCV. We will process all HSC sources with more than a predefined number of measurements in a single filter/instrument combination and compute a range of lightcurve features to determine the variability status of each source. At the end of the project, the first release of the Hubble Catalog of Variables will be made available at the Mikulski Archive for Space Telescopes (MAST) and the ESA Science Archives. The variability detection pipeline will be implemented at the Space Telescope Science Institute (STScI) so that updated versions of the HCV may be created following the future releases of the HSC. © Copyright International Astronomical Union 2017.

Deliverable D10.1 - "BlueBRIDGE Resources Federation Facilities" reports the release of the BlueBRIDGE facilities for integration of resources from external infrastructures and management of integrated resources. The deliverable covers the first nine months of the BlueBRIDGE project. An update to this deliverable is expected at project month M28 with Deliverable D10.2.

Quality Assurance is an important task within the scope of any IT project. The implementation of such activity is usually defined through a Quality Plan. This deliverable is the BlueBRIDGE Quality Plan. The objective of this deliverable is to provide the consortium with a practical guide for collaboration within the BlueBRIDGE project. The resulting Quality Plan covers many activities by gathering procedures from the varied managerial and technological aspects of the project. The ultimate objective of this Quality Plan is to ensure the production of concrete and high-quality results in line with the project plans.

Earth-Science data are composite, multi-dimensional and of significant size, and as such, continue to pose a number of ongoing problems regarding their management. With new and diverse information sources emerging as well as rates of generated data continuously increasing, a persistent challenge becomes more pressing: To make the information existing in multiple heterogeneous resources readily available. The widespread use of the XML data-exchange format has enabled the rapid accumulation of semi-structured metadata for Earth-Science data. In this paper, we exploit this popular use of XML and present the means for querying metadata emanating from multiple sources in a succinct and effective way. Thereby, we release the user from the very tedious and time consuming task of examining individual XML descriptions one by one. Our approach, termed Meta-Array Data Search (MAD Search), brings together diverse data sources while enhancing the user-friendliness of the underlying information sources. We gather metadata using different standards and construct an amalgamated service with the help of tools that discover and harvest such metadata; this service facilitates the end-user by offering easy and timely access to all metadata. The main contribution of our work is a novel query language termed xWCPS, that builds on top of two widely-adopted standards: XQuery and the Web Coverage Processing Service (WCPS). xWCPS furnishes a rich set of features regarding the way scientific data can be queried with. Our proposed unified language allows for requesting metadata while also giving processing directives. Consequently, the xWCPS-enabled MAD Search helps in both retrieval and processing of large data sets hosted in an heterogeneous infrastructure. We demonstrate the effectiveness of our approach through diverse use-cases that provide insights into the syntactic power and overall expressiveness of xWCPS. We evaluate MAD Search in a distributed environment that comprises five high-volume array-databases whose sizes range between 20 and 100 GB and so, we ascertain the applicability and potential of our proposal. © 2015 World Scientific Publishing Company.

D4Science II project aims to serve a set of different scientific communities under five (5) pre-identified scenarios, that consist of a set of users, applications and resources. In order for these scenarios to be realised on an interoperating eInfrastructures landscape, case-specific software implementation is required. This implementation is targeting (a) the migration or full implementation of applications that reside on the "outer" infrastructures in the new landscape and (b) the implementation of new functionality on gCube in order for the latter to cope with user requirements coming from NA5 tasks. The progress of the design and implementation of these components is being reported in this deliverable, which has the form of an on-line document produced by the processing of the thread of tickets managed in the TRAC system of the project that relate to the JRA2 tasks

Interoperability is one of the most challenging issues in the design and operation of large-scale computing infrastructures for multidisciplinary research. It requires solutions that can "embrace" heterogeneity, i.e. accommodate multiple incarnations of similar resources, as well as "hide" it, i.e. provide consumers with a homogeneous view of diverse resources. This paper overviews the measures put in place in the D4Science infrastructure to address a range of interoperability problems.

One of the objectives of the D4Science-II project is to serve very different and challenging scientific scenarios by providing the communities involved in them with innovative research environments. These environments will materialise in (i) a set of Virtual Research Environments, i.e. virtual laboratories providing the community they are conceived for with the set of data sources and facilities needed to accomplish their research tasks, and (ii) a set of Virtual Organisations, i.e. organised pool of actors and resources of various genre supporting an highly controlled sharing toward the building of Virtual Research Environments. This deliverable document the activities performed to satisfy the requirements of each available Virtual Organization and Virtual Research Environment so as to lead to a fully functional environment which offers all the available functional provided by the D4Science system.

Digital Library (DL) interoperability requires addressing a variety of issues associated with functionality. We report on the analysis and solutions identified by the Functionality Working Group of the DL.org project during its deliberations on DL interoperability. Ultimately, we hope that work based on our perspective will lead to improved architectures and software, as well as to greater interoperability, for next-generation DL systems. © 2010 Springer-Verlag Berlin Heidelberg.

This deliverable documents the methodology defined to identify, evaluate and classify the actual and potential risks the D4Science-II consortium and its related activities might be confronted with. In particular, the deliverable presents the adopted risk management methodology by detailing its different phases, procedures, tools, and actors involved. The deliverable relies on the procedures and experiences resulting from the D4Science project.

The realisation of a knowledge ecosystem requires the identification and deployment of a set of interoperability approaches and solutions making the interaction among the resources partaking to it feasible. The interoperability scenarios to be addressed depend on a set of factors including the type of resources involved, the kind of interaction to be realised, the technologies these resources have been implemented with. This deliverable describes a portfolio of standards (de jure or de facto), approaches and solutions that have been discussed and identified in the context of a working group operated by the D4Science-II project having as members representatives of the AquaMaps, D4Science, DRIVER, FAO, GENESI-DR and INSPIRE data infrastructures and resource providers. This working group surveyed the characteristics of the resources offered by each infrastructure as well as the standards and approaches put in place by them to "expose" their resources and simplify their consumption from third parties.

This report describes the achievements of the D4Science activities with respect to the planned objectives for the period January - March 2008. Section 1 provides a summary view of these achievements grouped into four activity areas: coordination and management, outreach, service and joint research. Section 2 details these achievements by reporting on the progresses done in the context of each activity area per constituent work package. Section 2.5 presents performance indicators measuring various aspects of the performed activities. Section 4 concludes this periodic report by summarising the main events occurred in the reporting period.

This document reports on the DILIGENT project's dissemination activities performed during the third year and the 3-month extension of the project (months 25-39). It provides brief background information on the concepts that guide dissemination in DILIGENT and introduces both the activities performed during this period and the material and instruments produced. Furthermore future activities and foreseen actions, that relate to the project and go beyond its end, are presented

D4Science provides production-quality facilities for creating and managing (VREs) based on an e-infrastructures composed of shared computational, storage, data and service resources. Through this, it enables scientists to organize, retrieve, access and analyse heterogeneous and widely distributed information in order to generate new knowledge.

This report describes the achievements of the D4Science activities with respect to the planned objectives for the period January - March 2008. Section 1 provides a summary view of these achievements grouped into four activity areas: coordination and management, outreach, service and joint research. Section 2 details these achievements by reporting on the progresses done in the context of each activity area per constituent work package. Section 2.5 presents performance indicators measuring various aspects of the performed activities. Section 4 concludes this periodic report by summarising the main events occurred in the reporting period.

gCube Information Retrieval Engine differentiates from federated search. Data and services are scattered over the infrastructure instead of being contained in confined sub-sections, made accessible via narrow interfaces. Grid, where gCube runs, is not meant for interactive work, but offers a vast pool of resources for processing large amounts of information. In such domain it comes as natural consequence the preference of machinery that can employ the afforementioned resources for offering a different range of services, over a traditional search facility.

The tutorial discusses the core ideas of building digital libraries on distributed infrastructures and the related architectural options. The main part of the tutorial revolves around how core DL functionality like Digital Library Management, Content and Collection Management, Metadata Management and Brokering, Search and Retrieval and Advanced Services (Personalization, Annotation, etc.) can be built by exploiting P2P and Grid technological frameworks. For each of the topics the key challenges are discussed together with possible solutions for the challenges and the lessons learned in implementing these solutions in concrete projects. The solutions are illustrated with concrete examples and demos from the projects DILIGENT, BRICKS, and DELOS as well as from other DL-related projects. Target Audience: The tutorial is mainly targeted towards researchers and practitioners that are working in the area of digital libraries, digital library architectures, and innovative digital library services. Furthermore, the tutorial will also be an opportunity for other players to gain insights in the area of current developments in the area of next generation digital library architectures and new applications of Grid technology and the Peer-to-peer paradigm. Level of experience required: Introductory to intermediate.

In large-scale distributed retrieval, challenges of latency, heterogeneity, and dynamicky emphasise the importance of infrastructural support in reducing the development costs of state-of-the-art solutions. We present a service-based infrastructure for distributed retrieval which blends middleware facilities and a design framework to 'lift' the resource sharing approach and the computational services of a European Grid platform into the domain of e-Science applications. In this paper, we give an overview of the DILIGENT Search Framework and illustrate its exploitation in the field of Earth Science. © Springer-Verlag Berlin Heidelberg 2007.

Digital Libraries are now envisioned as flexible systems set up by virtual organizations for supporting collaboration among its members. The sustainability of this new paradigm strongly relies on the two major capabilities: (i) controlled sharing of content, services and computing resources across organizations and (ii) on-demand creation of digital libraries throught the dynamic aggregation of the necessary shared resources. This tutorial will provide an overview of the solutions that can be used to implement this vision, focusing in particular on the exploitation of grid technologies and infrastructures. The solutions presented will be exemplified by presenting how they have been concretely put in practice in deploying DILIGENT (http://www.diligentproject.org), an infrastructure for supporting the creation of on-demand, transient digital libraries. The DILIGENT functionality will be exemplified by showing two digital libraries that have been created using this infrastructure: one for supporting the preparation of courses and other teaching activities in the Culture-Heritage sector and the other one supporting the process of reports preparation in the Earth Observation sector. Demonstrators will also be available to illustrate the realization of specific functionalities like image features extractions, video watermarking, and more low level functionality implemented to support the on-demand creation and management of digital libraries, like dynamic deployment and configuration of web services on remote hosting nodes belonging to the infrastructure.

This document reports on the DILIGENT project's dissemination activities performed during the second year of the project (months 13-24). It provides brief background information on the concepts that guide dissemination in DILIGENT and introduces both the activities performed during this period and the material and instruments produced. Furthermore planned activities and foreseen actions for the last year of the project are introduced

This document reports on the DILIGENT project's dissemination activities performed during the second year of the project (months 13-24). It provides brief background information on the concepts that guide dissemination in DILIGENT and introduces both the activities performed during this period and the material and instruments produced. Furthermore planned activities and foreseen actions for the last year of the project are introduced.

This document contains a full report on the DILIGENT project's dissemination activities performed during the first 12-month period of the project. It provides brief background information on the concepts that guide dissemination in DILIGENT and introduces both the activities performed during this period and the material and instruments produced.

This document describes the DILIGENT Project dissemination plan, which will serve as the guideline for the Dissemination and Liaison Activities during the remaining 30 months of the project. This plan handles both one-way traditional or electronically supported dissemination activities, as well as interactive collaborations between the DILIGENT project and selected relevant task forces or user communities, by proposing steps to be taken in a realistic, cost effective manner. It highlights the opportunities to be exploited, proposes the instruments to be utilized and the actions to be taken and sets the rules for facilitating both the sustainable development of the project's outcome and the reuse of technology and knowledge produced by experts worldwide.

This document contains a full report on the DILIGENT project's dissemination activities performed during the first 12-month period of the project. It provides brief background information on the concepts that guide dissemination in DILIGENT and introduces both the activities performed during this period and the material and instruments produced.

This document describes the DILIGENT Project dissemination plan, which will serve as the guideline for the Dissemination and Liaison Activities during the remaining 30 months of the project. This plan handles both one-way traditional or electronically supported dissemination activities, as well as interactive collaborations between the DILIGENT project and selected relevant task forces or user communities, by proposing steps to be taken in a realistic, cost effective manner. It highlights the opportunities to be exploited, proposes the instruments to be utilized and the actions to be taken and sets the rules for facilitating both the sustainable development of the project's outcome and the reuse of technology and knowledge produced by experts worldwide.

The globally observed recession of mobile services market has pushed mobile network operators into looking for opportunities to provide value-added services on top of their high cost infrastructures. Latest advances in self and network-assisted positioning technologies, enable the provision of services that make use of the actual mobile user location. This paper presents the key points and considerations of a detailed approach for designing, developing and evaluating a very low-cost infrastructure, capable of providing tourism content related location-based services. The main effort is taken into allowing the potential integration of various market and technology stakeholders into such services, thus supporting open business models, while at the same time safeguarding end-user privacy.