2020
Contribution to book  Open Access

Data Processing and Analytics for Data-Centric Sciences

Candela L., Coro G., Lelii L., Panichi G., Pagano P.

oopen science  data analytics  virtual research envirnonemt 

The development of data processing and analytics tools is heavily driven by applications, which results in a great variety of software solutions, which often address specific needs. It is difficult to imagine a single solution that is universally suitable for all (or even most) application scenarios and contexts. This chapter describes the data analytics framework that has been designed and developed in the ENVRIplus project to be (a) suitable for serving the needs of researchers in several domains including environmental sciences, (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, and (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: Towards Interoperable Research Infrastructures for Environmental and Earth Sciences. A Reference Model Guided Approach for Common Challenges., edited by Zhao Z.; Hellström M., pp. 176–191, 2020



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Projects (via OpenAIRE)

ENVRI PLUS
Environmental Research Infrastructures Providing Shared Solutions for Science and Society


OpenAIRE
BibTeX entry
@inbook{oai:it.cnr:prodotti:426058,
	title = {Data Processing and Analytics for Data-Centric Sciences},
	author = {Candela L. and Coro G. and Lelii L. and Panichi G. and Pagano P.},
	doi = {10.1007/978-3-030-52829-4_10},
	booktitle = {Towards Interoperable Research Infrastructures for Environmental and Earth Sciences. A Reference Model Guided Approach for Common Challenges., edited by Zhao Z.; Hellström M., pp. 176–191, 2020},
	year = {2020}
}