Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloExploring the depths of the global earth observation system of systems
Anno di pubblicazione2017
Formato
  • Elettronico
  • Cartaceo
Autore/iMax Craglia, Jiri Hradec, Stefano Nativi, Mattia Santoro
Affiliazioni autoriEC-JRC, EC-JRC, CNR-IIA, CNR-IIA
Autori CNR e affiliazioni
  • STEFANO NATIVI
  • MATTIA SANTORO
Lingua/e
  • inglese
AbstractBig Earth Data-Cube infrastructures are becoming more and more popular to provide Analysis Ready Data, especially for managing satellite time series. These infrastructures build on the concept of multidimensional data model (data hypercube) and are complex systems engaging different disciplines and expertise. For this reason, their interoperability capacity has become a challenge in the Global Change and Earth System science domains. To address this challenge, there is a pressing need in the community to reach a widely agreed definition of Data-Cube infrastructures and their key features. In this respect, a discussion has started recently about the definition of the possible facets characterizing a Data-Cube in the Earth Observation domain. This manuscript contributes to such debate by introducing a view-based model of Earth Data-Cube systems to design its infrastructural architecture and content schemas, with the final goal of enabling and facilitating interoperability. It introduces six modeling views, each of them is described according to: its main concerns, principal stakeholders, and possible patterns to be used. The manuscript considers the Business Intelligence experience with Data Warehouse and multidimensional "cubes" along with the more recent and analogous development in the Earth Observation domain, and puts forward a set of interoperability recommendations based on the modeling views.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da21
Pagine a46
Pagine totali-
RivistaBig earth data (Online)
Attiva dal 2017
Editore: Taylor & Francis - [Abingdon]
Paese di pubblicazione: Regno Unito
Lingua: inglese
ISSN: 2574-5417
Titolo chiave: Big earth data (Online)
Titolo proprio: Big earth data
Numero volume della rivista1
Fascicolo della rivista1-2
DOI10.1080/20964471.2017.1401284
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)-
Parole chiaveMachine learning, GEOSS, data management, neural networks, word embedding
Link (URL, URI)http://www.tandfonline.com/doi/abs/10.1080/20964471.2017.1401284
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • IIA — Istituto sull'inquinamento atmosferico
Moduli/Attività/Sottoprogetti CNR
  • TA.P06.027.001 : Condivisione delle informazioni geospaziali e della conoscenza ambientale (GENS)
Progetti Europei
Allegati
published version (documento privato )
Tipo documento: application/pdf