scholarly journals Virtual research environments as-a-service by gCube

2016 ◽  
Author(s):  
Massimiliano Assante ◽  
Leonardo Candela ◽  
Donatella Castelli ◽  
Gianpaolo Coro ◽  
Lucio Lelii ◽  
...  
Keyword(s):  
Information Systems ◽  
Data Management ◽  
Large Scale ◽  
Software System ◽  
Data Services ◽  
Continuous Evolution ◽  
Research Environments ◽  
Data Infrastructures ◽  
Hybrid Data ◽  
Oriented Research

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.

scholarly journals Virtual research environments as-a-service by gCube

2016 ◽  
Author(s):  
Massimiliano Assante ◽  
Leonardo Candela ◽  
Donatella Castelli ◽  
Gianpaolo Coro ◽  
Lucio Lelii ◽  
...  
Keyword(s):  
Information Systems ◽  
Data Management ◽  
Large Scale ◽  
Software System ◽  
Data Services ◽  
Continuous Evolution ◽  
Research Environments ◽  
Data Infrastructures ◽  
Hybrid Data ◽  
Oriented Research

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.

scholarly journals Managing Audio Monitoring Data with SIMON – Concept for Data Administration, Online Repository and Dissemination

2020 ◽  
Vol 4 ◽  
Author(s):  
Christian Köhler
Keyword(s):  
Data Management ◽  
Large Scale ◽  
Application Programming Interface ◽  
Automated Analysis ◽  
Task Group ◽  
Monitoring Data ◽  
Data Collector ◽  
Darwin Core ◽  
Data Infrastructures ◽  
Biodiversity Information

Automated observations of natural occurrences play a key role in monitoring biodiversity worldwide. With the development of affordable hardware like the AudioMoth (Hill et al. 2019) acoustic logger, large scale and long-term monitoring has come within reach. However, data management and dissemination of monitoring data remain challenging, as the development of software and the infrastructure for the management of monitoring data lag behind. We want to fill this gap, providing a complete audio monitoring solution from affordable audio monitoring hardware, custom data management tools and storage infrastructure based on open source hard- and software, biodiversity information standards and integrable interfaces. The Scientific Monitoring Data Management and Online Repository (SIMON) consists of a portable data collector and a connected online repository. The data collector, a device for the automated extraction of the audio data from the audio loggers in the field, stores the data and metadata in an internal cache. Once connected to the internet via WiFi or a cable connection, the data are automatically uploaded to an online repository for automated analysis, annotation, data management and dissemination. To prevent SIMON from becoming yet another proprietary storage, the FAIR principles (Findable, Accessible, Interoperable, and Re-usable) Wilkinson et al. (2016) are at the very core of data managed in the online repository. We plan to offer an API (application programming interface) to disseminate data to established data infrastructures. A second API will allow the use of external services for data enrichment. While in the planning phase, we would like to take the opportunity to discuss with domain experts the requirements and implementation of different standards—namely ABCD (Access to Biological Collections Data task group, Biodiversity Information Standards (TDWG) 2007), Darwin Core (Darwin Core Task Group, Biodiversity Information Standards (TDWG) 2009) and Darwin Core Archive (Remsen et al. 2017)—connecting to external services and targeting data infrastructures.

scholarly journals Realising Virtual Research Environments by Hybrid Data Infrastructures: the D4Science Experience

2014 ◽  
Author(s):  
Leonardo CANDELA ◽  
Pasquale PAGANO ◽  
Donatella CASTELLI ◽  
Andrea MANZI
Keyword(s):  
Research Environments ◽  
Data Infrastructures ◽  
Hybrid Data

A Bridge Too Far?

2018 ◽  
Author(s):  
Charlotte P. Lee ◽  
Kjeld Schmidt
Keyword(s):  
Information Systems ◽  
Science And Technology Studies ◽  
Large Scale ◽  
Cooperative Work ◽  
Computer Supported Cooperative Work ◽  
Practical Action ◽  
Systems Research ◽  
Information Infrastructures ◽  
Information Systems Research ◽  
Critical Investigation

The study of computing infrastructures has grown significantly due to the rapid proliferation and ubiquity of large-scale IT-based installations. At the same time, recognition has also grown of the usefulness of such studies as a means for understanding computing infrastructures as material complements of practical action. Subsequently the concept of “infrastructure” (or “information infrastructures,” “cyberinfrastructures,” and “infrastructuring”) has gained increasing importance in the area of Computer-Supported Cooperative Work (CSCW) as well as in neighboring areas such as Information Systems research (IS) and Science and Technology Studies (STS). However, as such studies have unfolded, the very concept of “infrastructure” is being applied in different discourses, for different purposes, in myriad different senses. Consequently, the concept of “infrastructure” has become increasingly muddled and needs clarification. The chapter presents a critical investigation of the vicissitudes of the concept of “infrastructure” over the last 35 years.

scholarly journals PowerSystems.jl — A power system data management package for large scale modeling

SoftwareX ◽  
2021 ◽  
Vol 15 ◽  
pp. 100747
Author(s):  
José Daniel Lara ◽  
Clayton Barrows ◽  
Daniel Thom ◽  
Dheepak Krishnamurthy ◽  
Duncan Callaway
Keyword(s):  
Power System ◽  
Data Management ◽  
Large Scale ◽  
Scale Modeling ◽  
System Data ◽  
Large Scale Modeling

Distributed-to-Centralized Data Management: A New Sense of Large-Scale ICT Management of Smart City IoT Networks

2020 ◽  
Vol 3 (3) ◽  
pp. 76-82
Author(s):  
Amir Sinaeepourfard ◽  
John Krogstie ◽  
Souvik Sengupta
Keyword(s):  
Data Management ◽  
Smart City ◽  
Large Scale
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