OSGeo Vision for UN-GGIM

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The United Nations Programme on Global Geospatial Information Management (GGIM) is an inter-governmental mechanism to consult on issues related to global geospatial information.
= Emerging Trends in Geospatial Information Management =
The perspective from the Open Source Geospatial Foundation (OSGeo).
== Background ==
OSGeo set out to support and promote the Open Source development in 2006. Initially starting with a very software centric perspective OSGeo members soon developed a broader perspective on Openness in the geospatial realm. This includes access to geospatial data, especially created and maintained by the public administration. 
Open Source is a legal licencing model which does not restrict individual's, government's and industry user's rights as proprietary licenses do but instead empowers users and protects their investments. Several Open Data models are currently emerging following similar principles of Open Source.
== Current Development ==
Open Source has developed into a widely recognized business model supporting the creation, analysis and dissemination of geospatial data. This includes opening up of algorithms independent of specific software packages, making analysis more transparent than ever before. This trend will continue and permeate the majority of software creation processes eventually replacing proprietary black box systems eliminating the dangers of vendor lock-in. Different areas of work and levels of specialization require their own time to evolve precluding the prediction of a distinct time frame. Taking current transitions into account within the next 5 year the larger number of geospatial web publication systems will run exclusively on Open Source. In the following five years Open Source and cloud deployment will also dominantly permeate analysis and processing. 
== Data Persistence ==
Over the past year the OSGeo Foundation has more and more recognized the importance of data as the heart and core for anything geospatial and Software increasingly becoming a means to add value by leveraging this spatial data. Proprietary business models put much more focus on the software as a product, making profits by requiring users to continuously upgrade, regardless of the need of the underlying data. But especially in the geospatial domain data needs to have persistence to allow for temporal analysis in years to come.
== Data Access ==
It is hard to prove that a change in policy will achieve results until the change has taken effect. Even then other factors can have strong influence on the results. Having said that it is even more important to understand that all studies on the effects of opening data access invariably show that this improves all aspects of information management. This includes disaster management, public safety, environmental sustainability and is also at the core of good governance and transparency. On the other hand all efforts at restricting access to data impede development, be it on a short term as in disaster alleviation or longer term when used as basis for improving social cohesion in communities. Improving data access applies to all themes and scales ranging from local, through national and up to global level. 
Digital data access also touches very new privacy issues which have raised discussion at all levels. Data is collected through social networks, multinational corporations and governments equally and in all cases transparency is key to good governance, again requiring open data access in order to allow control by independent instances.
== Economic Development ==
Open Source was often misunderstood to be anti-business and thus also undermining economic growth strategies. But quite the opposite is true. Open Source avoids monopolies, supports diversity, allows easy access to markets and in a positive sense is a perfect fit for the globalized economy. Instead of damaging the economy it empowers new market players to easily access markets and produce improved offerings. Therefore an Open Source policy will support strategic agendas of economic growth and in the long run also foster social cohesion. 
One source of resistance by government data producers against releasing data freely are short sighted economic considerations. During a phase of privatization in governments geospatial data was recognized as a potential resource of income. In effect this has never really funded the creation of the data but only covered a fraction of the production cost. It is out of question to privatize or completely outsource geospatial data management because it is the foundation of one of the most important administrative tasks of governments. Instead of trying to raise money by selling geospatial base data after the fact, the cost must be shifted to those who cause change in the environment, typically capitalized private undertakings. With the advent of geospatially enabled sensors, GPS, bi-directionally communicating traffic navigation systems and similar technologies a lot of geospatial data is raised which can be used statistically both to create new insights and quality assure geospatial base data. 
All of these developments are very recent and still need to be comprehensibly communicated to the political level in order to allow this level to decide helpful policies. 
== Collaboration ==
Open Source and Open Standards support collaboration by making sharing and exchanging of both software and data easier. In turn, collaboration is the primary motor for software development and reason for the high quality and fast innovation cycle of successful projects. Truly open standards evolve together with the technical capabilities and the needs of the communities developing and applying them. They do not restrict innovation but instead make sure that data can be exchanged - which is the foundation for collaboration. The recent phenomenon of Crowd Sourcing would not have been possible without both Open Source Software and Open Standards. Crowd Sourcing is still an emerging phenomenon but has already proven to be an important asset for disaster management and an indispensable aspect of good governance.
Collaboration improves data quality. This has been widely demonstrated by successful Open Source software projects with good governance and high quality. Cross border collaboration ensures that the quality of the data on both sides of the border is double checked and improved. The same process on a much broader level, between scales and also cross thematically will develop when crowd sourced data is organizationally intersected with administrative and governmental data as is already frequently happening at local level. 
This development will take more concrete forms within the next 5 years and be commonplace within the next 10 years. Exceptions might be seen in areas where national strategic economic agendas focus on supporting proprietary software industry or where environmental sustainability and good governance are not on the primary political agenda. Open Source and Open Data models will level the playing field for NGOs, developing nations and enable a truly global and just economy.