2017 Contribution to journal Open Access

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2017 Journal article Open Access

Making the development and deployment of virtual research environments easy and effective
Candela L., Castelli D., Pagano P.
Making the Development and Deployment of Virtual Research Environments Easy and Effective.Source: ERCIM news 109 (2017).
Project(s): BlueBRIDGE

See at: ercim-news.ercim.eu | ISTI Repository | CNR ExploRA

2017 Report Open Access

SoBigData - Resource adaptation to register to the e-infrastructure 1. Deliverable D10.8
Manghi P., Candela L., Pagano P.
This deliverable reports the experiences of partners from different infrastructures at integrating their services, methods, and applications as SoBigData resources. The first section describes the general integration patterns, while the section section reports the experiences from the individual partners, revealing the effort required, in terms of time and technical complexity, and earned benefits.Source: Project report, SoBigData, Deliverable D10.8, pp.1–24, 2017
Project(s): SoBigData

See at: ckan-sobigdata2.d4science.org | ISTI Repository | CNR ExploRA

2017 Report Open Access

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2017 Report Open Access

SoBigData e- Infrastructure release plan 2
Candela L., Manghi P., Pagano P.
This deliverable refines the plan as described in deliverable D10.2, characterizing the release and development of the SoBigData e-Infrastructure in the second year. This is the second of three versions of the plan, each describing the actions associated with a specific version of the infrastructure to be made available at M12 (August 2016), M24 (August 2017) and M36 (August 2018). In particular, the deliverable describes the current status of the e-infrastructure and focuses on the plan leading to the second release of the SoBigData e-Infrastructure at M24.Source: Project report, SoBigData, Deliverable D10.3, pp.1–30, 2017
Project(s): SoBigData

See at: ckan-sobigdata2.d4science.org | ISTI Repository | CNR ExploRA

2017 Conference article Open Access

Enacting Open Science by gCube
Assante M., Candela L., Castelli D., Coro G., Mangiacrapa F., Pagano P., Perciante C.
The Open Science movement is promising to revolutionise the way science is conducted with the goal to make it more fair, solid and democratic. This revolution is destined to remain just a wish if it is not supported by changes in culture and practices as well as in enabling technologies. This paper describes the gCube offering to enact Open Science-friendly Virtual Research Environments. In particular, the paper describes how a complete solution suitable for realising Open Science practices is achieved by a social networking collaborative environment in conjunction with a shared workspace, an open data analytics platform, and a catalogue enabling FAIR principles on every research artefact.Source: IWSG 2017 International Workshop on Science Gateways, Poznan, Poland, 19/06/2017-21/06/2017
Project(s): AGINFRA PLUS

See at: ceur-ws.org | ISTI Repository | CNR ExploRA

2017 Journal article Open Access

HyWare: a HYbrid Workflow lAnguage for Research E-infrastructures
Candela L., Giannotti F., Grossi V., Manghi P., Trasarti R.
Research e-infrastructures are "systems of systems", patchworks of tools, services and data sources, evolving over time to address the needs of the scientific process. Accordingly, in such environments, researchers implement their scientific processes by means of workflows made of a variety of actions, including for example usage of web services, download and execution of shared software libraries or tools, or local and manual manipulation of data. Although scientists may benefit from sharing their scientific process, the heterogeneity underpinning e-infrastructures hinders their ability to represent, share and eventually reproduce such workflows. This work presents HyWare, a language for representing scientific process in highly-heterogeneous e-infrastructures in terms of so-called hybrid workflows. HyWare lays in between "business process modeling languages", which offer a formal and high-level description of a reasoning, protocol, or procedure, and "workflow execution languages", which enable the fully automated execution of a sequence of computational steps via dedicated engines.Source: D-Lib magazine 23 (2017): 8–11. doi:10.1045/january2017-candela
DOI: 10.1045/january2017-candela
Project(s): SoBigData
Metrics:

See at: D-Lib Magazine | ISTI Repository | OpenAIRE | CNR ExploRA

2017 Journal article Open Access

White paper on research data service discoverability
Thanos C., Klan F., Kriticos K., Candela L.
This White Paper reports the outcome of a Workshop on "Research Data Service Discoverability" held in the island of Santorini (GR) on 21-22 April 2016 and organized in the context of the EU funded Project "RDA-E3". The Workshop addressed the main technical problems that hamper an efficient and effective discovery of Research Data Services (RDSs) based on appropriate semantic descriptions of their functional and non-functional aspects. In the context of this White Paper, by RDSs are meant those data services that manipulate/transform research datasets for the purpose of gaining insight into complicated issues. In this White Paper, the main concepts involved in the discovery process of RDSs are defined; the RDS discovery process is illustrated; the main technologies that enable the discovery of RDSs are described; and a number of recommendations are formulated for indicating future research directions and making an automatic RDS discovery feasible.Source: Publications 5 (2017). doi:10.3390/publications5010001
DOI: 10.3390/publications5010001
Project(s): RDA Europe
Metrics:

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2017 Conference article Open Access

Virtual research environments as-a-Service by gCube
Assante M., Candela L., Castelli D., Coro G., Lelii L., Pagano P.
Science is in continuous evolution and so are the methodologies and approaches scientists tend to apply by calling for appropriate supporting environments. This is in part due to the limitations of the existing practices and in part due to the new possibilities offered by technology advances. gCube is a software system promoting elastic and seamless access to research assets (data, services, computing) across the boundaries of institutions, disciplines and providers to favour collaborative- oriented research tasks. Its primary goal is to enable Hybrid Data Infrastructures facilitating the dynamic definition and operation of Virtual Research Environments. To this end, it offers a comprehensive set of data management commodities on various types of data and a rich array of "mediators" to interface well-established Infrastructures and Information Systems from various domains. Its effectiveness has been proved by operating the D4Science.org infrastructure and serving concrete, multidisciplinary, challenging, and large scale scenarios. This paper gives an overview of the gCube system.Source: 8th International Workshop on Science Gateways, pp. 2–6, Rome, Italy, 8-10 June 2016
Project(s): BlueBRIDGE

See at: ceur-ws.org | ISTI Repository | CNR ExploRA

2017 Conference article Open Access

Towards a global record of stocks and fisheries
Tzitzikas Y., Marketakis Y., Minadakis N., Mountantonakis M., Candela L., Mangiacrapa F., Pagano P., Perciante C., Castelli D., Taconet M., Gentile A., Gorelli G.
The collation of information for the monitoring of fish stocks and fisheries is a difficult and time-consuming task, as the information is scattered across different databases and is modelled using different formats and semantics. Our purpose is to offer a unified view of the existing stocks and fisheries information harvested from three different database sources (FIRMS, RAM and FishSource), by relying on innovative data integration and manipulation facilities. In this paper, we describe the activities carried out to realize the Global Record of Stocks and Fisheries (GRSF) which aims at offering an integrated and enriched view on data about fish stocks and fisheries from the database sources. More specifically we describe the model, the workflow and the software components for producing GRSF records and make them easily available to the users.Source: 8th International Conference on Information and Communication Technologies in Agriculture, Food and Environment, pp. 328–340, Chania, Greece, 21-24 September 2017
Project(s): BlueBRIDGE

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2017 Report Open Access

PARTHENOS - Design of the joint resource registry. Deliverable D5.2 PARTHENOS
Aloia N., Candela L., Debole F., Frosini L., Lorenzini M., Pagano P.
The activity of design of the Joint Resource Registry is propaedeutic to the building phase of a comprehensive inventory of resources and is the result of two different activities: o A survey of resources (datasets, collections, infrastructures, services) available in the archaeological context; o The definition of the main entities for the PARTHENOS data model taking into account the ontology defined in T5.1. In this document, we present a description of the existing registries in the humanities area, derived from the analysis conducted in the first activity. The goal of the activity was to identify the main descriptive conceptual entities and features of existing resources that would be useful for the definition of the PARTHENOS Registry Data Model. This document is organized as follows: Section 2 describes the best-known standards used in the definition of registry models; Section 3 describes the survey carried out of existing registries in the thematic area of the PARTHENOS project; Section 4 contains a detailed description of the surveyed registries; Section 5 summarizes the main entities and functionalities of the analysed registries; Section 6 presents the PARTHENOS Joint Resource Registry Data Model; and finally, Section 7 presents the architecture of the Joint Resource Registry service that implements the model.Source: Project report, PARTHENOS, Deliverable D5.2, pp.1, 2017
Project(s): PARTHENOS

See at: ISTI Repository | www.parthenos-project.eu | CNR ExploRA

2017 Report Open Access

ENVRI PLUS - Data curation in system level sciences: initial design
Jeffery K. G., Zhao Z., Magagna B., Nieva De La Hidalga A. N. D. L. H., Candela L., Enell C., Hellstrom M., Hardisty A., Paxton C., Toussaint F.
Data curation is commonly the 'Cinderella' of ICT (Information and Communication Technologies). Usually, it receives little attention from researchers or managers and may be seen as a tedious chore to be done in wrapping up the research activity. Since research may well be continuous, such wrapping up may not occur. In contrast, many important research discoveries have been made by re-working old data and/or by comparison of old data with recently collected data. This is particularly true of environmental sciences where understanding the atmospheric, biospheric, hydrospheric and geospheric processes usually requires long-term observation and subsequent analysis. Furthermore, validation and re-validation of research results requires open and understandable access to the data used in the preparation of the original publication. Data curation is thus an important aspect of ENVRIplus and a key element of the ICT architectural and governance design. Data curation is integral to research methods (supporting, influencing, recording), workflows and processes and also integrates with all ICT activities through cataloguing and provenance. With an evolving policy of open access to data - as well as publications - and, in time, software developed from the open source movement - curation has become more visible and necessary. This deliverable reviews the state of the art and recommends architectural principles to be taken into account (along with the inputs on other topics) in the initial and subsequent architectural design phases of ENVRIplus.Source: Project report, ENVRI PLUS, Deliverable D8.1, 2017
Project(s): ENVRI PLUS

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2017 Report Open Access

BlueBRIDGE Data Management Plan: Intermediate version
Candela L., Castelli D., Pagano P.
This deliverable documents the BlueBRIDGE data management strategy. This strategy is going to be developed by producing three successive versions of this deliverable: a preliminary version at M6, an intermediate version at M18, a final version at M27. This intermediate version of the plan is completely diverse from the previous one since it follows the new guidelines for Data Management Plans published by the Commission on July 2016. It is organised around solutions and approaches aiming at making BlueBRIDGE data / datasets findable, accessible, interoperable and re-usable (FAIR). In particular, this version of the deliverable provides an overview of the data managed by the project by describing the purpose of the data collection/generation and its relation to the objectives of the project, the types and formats, any re-use of existing data as well as giving hints on "data utility", i.e. scenarios and stakeholders that might benefit from BlueBRIDGE data. Then the deliverable describes the specific solutions and approaches for making BlueBRIDGE data FAIR, namely (i) the provisioning of an array of catalogues including an "overall" one making it possible to associate suitable metadata to the data, (ii) the provisioning of several repositories for data thus to deal with the heterogeneity characterising the VREs, (iii) the support for standard and controlled vocabularies, and (iv) the promotion of practices favouring the re-use, e.g. licences making the data as open as possible. Finally, the deliverable concludes by discussing costs and resources underlying the data management just described and some preliminary thoughts on challenging issues like data security, legal and ethical issues.Source: Project report, BlueBridge, Deliverable D2.2, pp.1–34, 2017
Project(s): BlueBRIDGE

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2017 Report Open Access

ENVRI PLUS - Interoperable data processing for environmental ri projects: system design.
Candela L., Coro G., Pagano P., Panichi G, Atkinson M., Filgueira R., Bailo D., Enell C. F., Fiebig M., Haslinger F., Hellström M, Vermeulen A., Lankreijer H., Huber R., Joussaume S., Guglielmo F., Mendez V.
Data processing is a very wide area or domain because of a series of characteristics including the contexts resulting from diverse application scenarios, the great variety of processes to be enabled, the large set of enabling technologies and solutions. One of the consequences of this large variety is that each software solution for data processing only manages to address parts, i.e. it is difficult to imagine a single solution that is equally suitable for any (or even most) application scenarios and contexts. This deliverable illustrates that scope and diversity by reporting detailed practices and requirements from seven of the ENVRI RIs. It then describes the design of a single data processing solution that will help meet a substantial range of requirements in a representative range of contexts. That approach is conceived to be (a) suitable for serving the needs of scientists involved in ENVRI RIs, (b) open and extensible both with respect to the algorithms and methods it enables and the computing platforms it relies on to execute those algorithms and methods, (c) open-science-friendly, i.e. it is capable of incorporating every algorithm and method integrated into the data processing framework as well as any computation resulting from the exploitation of integrated algorithms into a "research object" catering for citation, reproducibility, repeatability and provenance.Source: Project report, ENVRI PLUS, Deliverable D7.1, pp.1–55, 2017
Project(s): ENVRI PLUS

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2017 Report Open Access

ENVRI PLUS - A development plan for common operations and cross-cutting services based on a network of data managers and developers. Work Package 5 - Reference Model Guided Ri Design
Jeffery K. G. J., Atkinson M., Zhao Z., Chen Y., Nieva De La Hidalga A., Hardisty A., Legre Y., Candela L., Bailo D., Loubrieu T., Magagna B.
ENVRIplus is - by its very nature - a heterogeneous distributed network of Research Infrastructures (RI) for providing the advanced supporting environments for environmental scientists. Thus, a key feature of any recommended conceptual architecture for RIs - for their own beneficial utilisation and also for RI interoperation - requires the recommendation of common operations and cross-cutting services to allow the researchers to perform their work effectively and efficiently and to allow access to RIs other than the one to which they are usually attached in order to encourage - where appropriate - multidisciplinary research. Identification of computational objects in the RM (Reference Model) of the ENVRI project provides a basis; the purpose of WP5 in ENVRIplus is 'providing a novel ENVRIPLUS Reference Model which should be developed not only based on the existing ENVRI RM but should also include the latest development insights from other successful RIs'1. Thus, a re-examination of the requirements from D5.1 within ENVRIplus [Atkinson et al. 2016] is the start point, wherever possible, for a proper matching with the (developing) ENVRI RM. These common aspects emerge from two directions: (1) the state of the art, which provides opportunities for utilisation in ENVRIplus and (2) the requirements, which provide the specifications of the services and operations needed by the users of the ENVRIplus RIs. The common aspects form a key basis to achieve the distributed, interoperating architecture recommended for ENVRIplus providing the RIs with an evolutionary direction for the individual RIs to adopt best practice and for them to become interoperable. The development plan provides a stepwise approach to achieve the architecture recommended for ENVRIplus.Source: Project report, ENVRI PLUS, Deliverable D5.4, 2017
Project(s): ENVRI PLUS

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2017 Report Open Access

ENVRIPlus - A model architecture for new ris to adopt and to act as a guide for existing ris in their development. Deliverable D5.5
Jeffery K. G., Atkinson M., Zhao Z., Chen Y., Nieva De La Hidalga A., Hardisty A., Candela L., Bailo D., Loubrieu T., Magagna B., Glaves H.
The major objective of ENVRIplus is to facilitate research in environmental science by encouraging movement towards a consistent and integrated view of data, processing and resources to meet emerging domain-specific and interoperation research needs. The adoption of common and cross-cutting ICT services by RIs (Research Infrastructures) reduces cost (re-use) and increases interoperation (standardisation). A key aspect of ENVRIplus is the reference architecture to be adopted by new RIs and towards which existing RIs should aim to align. Based on the ENVRI Reference Model, the architecture brings together all the aspects of the ICT (Theme 2) activities of ENVRIplus into a coherent framework to achieve those objectives. The architecture must sit within some constraints. ICT best practice is mandatory. Parallel initiatives in other ESFRI RIs and global consortia must be respected. Developments in e-Is (e- Infrastructures) provide opportunities for alternative deployment of applications. An appropriate interfacing mechanism between RIs and e-Is will provide for evolution of both RIs and e-Is while maintaining provision of service. Similarly, developments in VREs (Virtual Research Environments) offer improved opportunities for researchers (and other users) to access multiple RIs while appropriate interfacing will allow evolution of both RIs and VREs to sustain the consistent and integrated facilities built on the resources delivered by collaborating RIs. The degree of alignment with the architecture by RIs will improve their ability to present a research environment that supports research campaigns that need resources and capabilities from multiple RIs. The development of the ENVRIplus architecture is therefore continuous, and this deliverable (D5.5) presents the current state of progress at this point in the project. Further work on the RM (Reference Model) will provide specifications based on engineering and technology viewpoints at which time a conventional architectural design document can be produced.Source: Project report, ENVRI PLUS, Deliverable D5.5, pp.1–51, 2017
Project(s): ENVRI PLUS

See at: ISTI Repository | www.envriplus.eu | CNR ExploRA

2017 Report Open Access

PARTHENOS - D6.3 Report on the implementation of the Joint Resource Registry (interim)
Frosini L., Assante M., Dell'Amico A., Lelii L., Candela L., Pagano P.
The D6.3 Report on the implementation of the Joint Resource Registry documents the interim implementation of the Joint Resource Registry (JRR). It complements the D5.2 Report on the design of the Joint Resource Registry deliverable by providing details on how to interact with and exploit the functionalities it provides. The JRR hosts the PARTHENOS entities represented according to the PARTHENOS Entities Model defined in WP5. As such, it represents an information system for the PARTHENOS community and the PARTHENOS universe of tools and services designed for and released in the PARTHENOS infrastructure. This deliverable presents, in Section 2, the principles and guidelines that govern the implementation of the JRR which has been designed to support the persistence of the PARTHENOS Entities. The JRR is implemented as a tailored information system capable of satisfying the evolution of the model itself, the main features of which are described in section 3 since the facet based resource model is extensively referred to throughout this report. Entities, Resources, Facets and Relations are described in detail. Section 4 describes the set of technical components comprising the JRR and APIs, covering the architecture which includes the Resource Registry Service, Context Client, Schema Client, Publisher and Client. Section 5 provides information regarding how to interact with the Resource Registry Service by exploiting the Context and Schema Port Types. The REST APIs are also presented for each functionality. Section 6 covers the backend database, OrientDB, a Multi-Model Open Source NoSQL DBMS that brings together the power of graphs and the flexibility of documents into one scalable high-performance operational database. The final section provides information on the Studio GUI used by the Content Administrator for searching between the created types and inspection of their schema.Source: Project report, PARTHENOS, Deliverable D6.3, pp.1–53, 2017
Project(s): PARTHENOS

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2017 Report Open Access

AGINFRA PLUS - Open Science Data Analytics Technologies D3.1
Candela L., Cirillo R., Coro G., Lelii L., Pagano P., Panichi G., Scarponi P., Sinibaldi F.
Deliverable D3.1 "Open Science Data Analytics Technologies" is a deliverable of type Demonstrator meaning that it manifests in artefacts (software releases) other than reports. In particular, the deliverable is about the software realising the Data Analytics & Processing Layer of the AGINFRA+. This software is part of a large software system named gCube (www.gcube-system.org). The gCube system offers a large array of services supporting the entire lifecycle underlying a research activity (data management and collation, analytics, collaboration, sharing) and the possibility to combine these services in Virtual Research Environments1. In the context of AGINFRA PLUS the following gCube components have been primarily exploited, consolidated and enhanced to serve the analytics needs arising in the context of the project use cases. DataMiner, i.e. a service enacting its users to perform data analytics tasks by relying on an array of analytics methods and a distributed and heterogeneous computing infrastructure. This service is available by a web-based GUI as well as via a web-based API based on the OGC WPS standard. SAI (Statistical Algorithm Importer), i.e. a service enacting its users to make available their own analytics methods via the DataMiner service. In addition to that, the entire analytics solution made available for AGINFRA PLUS cases counts on (i) a shared workspace realising a cloud-based file manager for managing content of interest and sharing this content with co-workers, (ii) a social networking area enabling users to post messages and have discussions, (iii) a flexible catalogue enabling to publish and discover items of interest including "research objects" resulting from an analytics task. This technology is deployed in its latest version in every Virtual Research Environment supporting AGINFRA PLUS cases2. The major enhancements to the technology pertaining to AGINFRA PLUS have been included in three gCube major releases3 4.7 (October 2017), 4.8 (November 2017), and 4.9 (under production).In particular, with these releases a new"black-box" oriented approach (https://wiki.gcubesystem. org/gcube/Statistical_Algorithms_Importer:_Java_Project#Black_Box_Integration)has been envisaged and implemented to enact analytics method owners and developers to easily integrate theirsolutions into the DataMinerservice. Among the supported black-box typologies there is that for KNIME workflows, i.e. analytics methods implemented by a KNIME workflow. KNIME is among the key technologies supporting the Food Safety Risk Assessment cases. In order to enact the execution of KNIME-based black-boxes, the distributed computing part of the data analytics platform has been extended to integrate the KNIME execution engine. Other cases are counting on the same mechanism to integrate entire applications (WOFOST4) as well as Python-based methods.Source: Project report, AGINFRA PLUS, Deliverable D3.1, pp.1–4, 2017
Project(s): AGINFRA PLUS

See at: ISTI Repository | support.d4science.org | CNR ExploRA