The need for data sharing
Every day we access an enormous and continuous flow of information and much of it refers to a position or a specific place on the surface of our planet. This information is therefore, and by definition, georeferenced. Therefore, in the last 30 years, the amount of georeferenced data available has grown dramatically following the evolution of the communication means and due to the rapid development of spatial data capture technologies such as Global Positioning System (GPS), remote sensing images, sensors, etc (Philips et al., 1999).
Despite the fact that administrations and governments are recognizing that spatial information is important and must be part of the basic information infrastructure that need to be efficiently coordinated and managed for the interest of all citizens (Ryttersgaard, 2001), this huge amount of geospatial data is stored in different places, by different organizations and the vast majority of the data are not being used as effectively as they should.
This means that there is a strong need for availability and access to appropriate information. The development of databases and exchange of information are the conditions for creating the basis for a sustainable development and to support the information management needs for implementing and monitoring sustainable development policies and goals like the UN Millennium Development Goals (UNGIWG, 2007).
However, geospatial information is an expensive resource, it is time consuming to produce, and for this reason it is of high importance to improve the access and availability of data, and promote its reuse. Many of the decisions that different organization need to make depend on good and consistent georeferenced data, available and readily accessible (Rajabifard and Williamson, 2001).
Even if all technologies are ready, organizations and agencies around the world are still spending billions of dollars every year to produce, manage and use geographical data but without having the information they need to answer the challenges our world is facing (Rajabifard and Williamson, 2001). These authors also highlight the facts that most organizations and/or agencies need more data than they can afford, they often need data outside their jurisdictions, and the data collected by different organizations are often incompatible. This inevitably leads to inefficiencies and duplication of effort, and thus it is evident that countries can benefit both economically and environmentally from a better management of their data (UNGIWG, 2007; GSDI, 2004). In consequence, it is now essential to make these data easily available and accessible in order to give the opportunity to the user to turn them into understandable information.
Coastal, Marine and Maritime data sharing
The availability and easy access to a wide range of data on the oceans and coastal zones is one of the key aspects to support strategic decision-making regarding ICZM and maritime policies (e.g. EU ICZM, EU Integrated Maritime Policy, EU Marine Strategy Framework Directive, Barcelona convention, ICZM protocol for the Mediterranean, Bucharest convention,…). There is a vast quantity of data available from many sources (see further below for the Mediterranean and Black Seas) but gathering them for particular applications takes considerable effort. The establishment of appropriate coastal and marine data and information infrastructures is of highest importance.
The European efforts towards a Sustainable and Integrated Maritime Policy indeed highlight the development of three instruments (COM (2007) 575, SEC (2007) 1278):
- Maritime Surveillance (critical for the safe and secure use of marine space)
- Maritime Spatial Planning
- A comprehensive and accessible source of data and information
Spatial Data Infrastructures aim to realize this last instrument by integrating existing, but fragmented initiatives in order to facilitate access to primary data for users, either from public, or business, or academic, government or citizens sector.
This data should be compiled in a comprehensive and compatible system. Implementing a Spatial Data Infrastructure, following the INSPIRE Directive, implies that local geonodes must be developed, spatial data must be standardized and harmonization must take place in order to start sharing data.
Spatial Data Infrastructure for the Mediterranean and Black Seas
The PEGASO project is an example initiative for the Mediterranean and Black Seas that aims to build a shared ICZM Governance Platform with scientists and end-users, linked with new models of governance. The PEGASO ICZM Platform will be supported by the development of a Spatial Data Infrastructure (SDI) and the suite of sustainability assessment tools required for making multi-scale integrated assessments in the coastal zone.
Thus, a key objective of PEGASO is to set up a good SDI, where all data and indicators from PEGASO participants can be shared, using the different services which will be offered through its geoportal. The idea is to build a functional network of geonodes with all partners, supporting capacity in the South countries to co-develop and support existing geonodes and to build local/regional or national geonodes if requested by stakeholders. Data then will be easily accessible through a web portal that will also help in managing communication and dissemination of results amongst partners and the Shared ICZM platform components. PEGASO will support harmonization of data and metadata, which are key components to build assessment tools and to support the regional assessment on the Mediterranean and Black Sea basins.
Thus PEGASO will construct such an infrastructure by drawing on existing SDIs from project participants, such as SEXTANT from IFREMER and IODE, and extend their capabilities via easy Internet access to data. The PEGASO SDI will allow simple GIS manipulation by all users and the downloading of relevant data for more detailed local analysis. In order to further build capacity, special effort will be dedicated in the Project to support SDI and geonode construction amongst the participants, which require it.
The partners of PEGASO are highly involved in network for data harmonization and SDI creation (INSPIRE, GEO-GEOSS, ICAN, EMODNET, EIONET, etc), a network that will greatly facilitate data harmonization and as much as possible interoperability.
To address the PEGASO project strategic objectives (through a common SDI), PEGASO has conducted a survey on the levels of capacity, available data-infrastructures to implement an SDI and potential data and information sources (from the partner institutions and relevant EU projects). The results from this survey evidenced the presence of a wealth of information for the entire area covered by the project (e.g. African Marine Atlas and Emodnet including i.a. Emodnet Biology) and a great capacity within the consortium, with promising opportunities to share data and expertise between the partners. However some issues like scale differences, integration and standardization still have to be addressed and above all it is necessary first to achieve a common understanding and common view on how the SDI should deliver the objectives of the ICZM policies. For more information on the approach within the PEGASO consortium please find the deliverable of this task here.
- ↑ Phillips, A., Williamson, I., and Ezigbalike C., 1999. ‘Spatial Data Infrastructure Concepts’ in The Australian Surveyor, 44:1, pp. 20-28
- ↑ Ryttersgaard J. (2001) Spatial Data Infrastructure, Developing Trends and Challenges, International Conference on Spatial Information for Sustainable Development Proceedings, Nairobi, 8p., http://www.fig.net/pub/proceedings/nairobi/ryttersgaard-TS1-1.pdf
- ↑ 3.0 3.1 UNGIWG (2007) UNSDI Compendium - A UNSDI Vision, Implementation Strategy and Reference Architecture, 150p., http://www.ungiwg.org/docs/unsdi/UNSDI_Compendium_13_02_2007.pdf
- ↑ 4.0 4.1 Rajabifard A. and Williamson I.P. (2001) Spatial Data Infrastructures: Concept, SDI Hierarchy and Future directions, in Proceedings, of GEOMATICSʼ80 Conference, Tehran,Iran., 10p., http://repository.unimelb.edu.au/10187/1247
- ↑ GSDI, 2004. Spatial Data Infrastructure Cookbook v. 2.0. Global Spatial Data Infrastructure Association, viewed on 16 December 2004, http://www.gsdi.org/gsdicookbookindex.asp