PRESS RELEASE:- Castries, June 24, 2015- The OECS Commission recently conducted a virtual Geographical Information Strategy or GIS Symposium which is part of plans towards a Regional Geographic Data Strategy.
The virtual GIS symposium on Wednesday June 22nd 2016, is described as a pioneering initiative to lay the foundation for a fully developed regional data ecosystem.
Various agencies and individuals involved in data gathering particularly in the area of location data were part of the exercise.
The activity also intended to discuss the relationship between data and the location from which the data is acquired to help inform more effective interventions for social, economic and environmental development.
OECS Director General Dr. Didacus Jules says given the reality of today’s interconnected economies, data assimilation and the convergence of meaningful results is paramount to enable more informed decision making at all governance levels: “Member States have started incorporating technology enabled decision-support systems into the fabric of national development plans and the next step will involve the strategic harmonisation of data-ecosystems across all sectors and countries in our sub region. This will improve the region’s capacity to make informed decisions at both the national and regional level. It will also contribute significantly to the OECS’ ability to be more proactive and effective in shaping and managing the region’s development agenda. For the first time in the OECS, we have completed a comprehensive needs assessment as a tangible step on the path to a regional geographic data strategy.”
All OECS Member States, individuals and agencies in the development sector as well as others associated with data management are among those who stand to benefit.
The OECS Commission’s virtual Geographical Information Symposium also discussed harmonized technological platforms and standards as well as governance and communication systems for a cross fertilization of ideas to keep the data in its purest form and help avoid statistical errors.