The SDI for A Drought Observatory

A coherent workflow, from the data acquisition to the information delivering

The SDI built to support the DO is based on the two paradigms Open Innovation and FAIR.

The Open innovation concept consists of three pillars:

  • Open Source
  • Open Data
  • Open Access


FAIR is the acronym defining how should be information: Findable,    Accessible,    Interoperable,    Reusable

Moreover, the SDI responds to some fundamentals requirements: research data openness, interoperability, flexibility, scalability, responsiveness, specific user needs and skills.

Our user-oriented and process-based DO SDI is focused on the best use of climate and environmental data for drought assessment and their translation in information, instead of simple data sharing.

The DO SDI technological components are organized in typical client-server architecture and interact from the data provider’s download data process to the results representation to end users, following general OGC guidelines.

Data Cube

The geospatial Data Cube multi-dimensional approach allows the ingestion, storage, access, analysis, and use of large amounts of data elements inherently ordered according to shared attributes, one of which has to be their geospatial location (Strobl et al., 2017).

OGC Standards

OGC (Open Geospatial Consortium) standards are used in several elements developed into the DO SDI, starting from the data model, designed using Unified Modeling Language (UML) (ISO TC/211), to PostGIS open source software.

Data Model

The data model is developed following a participative approach among the researchers involved in data collection and analysis for the application schema implementation.

Platform Interoperability

To ensure the platform interoperability between geospatial data and services, three main services are considered in the general SDI architecture: catalog service, data service and processing service.

The design of the DO SDI

Open source softwares and a layered architecture for the DO monitoring framework optimization

Providers Layer Retrieving input data

Drought Framework Layer Managing metadata and processing stored data

Client-side Layer Results dissemination

All the three layers communicate through specific Representational State Transfer (REST) web services, following the SOA paradigm.

REST paradigm, even if only marginally considered in the OGC standards implementation (i.e. for the WMTS), is preferred to the Simple Object Access Protocol (SOAP) because it is lightweight and less client-side complex to manage by the users.

Furthermore, RESTful Web Services provide functions of data extraction and downloading in an effective and highly flexible way.

The Framework Layer Services

Spatial data ready to be re-used by any third-party client applications
The Framework Layer also supplies a suite of RESTful web services, developed using JAX-RS (Java API for RESTful Web Services), for retrieving stored data (inputs, intermediate and outputs) and handling the geospatial operations developed with PL/pgSQL (i.e. the extraction of raster portions from a given polygon, basic statistics, and models run).

The open source Comprehensive Knowledge Archive Network (CKAN) data-management platform and the GeoServer data-publishing web server, are respectively used to harvest the catalog and to publish data and metadata. CKAN supports ISO 19139 (Geographic information – Metadata – XML schema implementation) encoding for metadata description and it is also able to manage the OGC CSW and WMS standards.

The Drought Observatory project: a short card