The term "Open Data" is currently being used in many different contexts and to describe different aspects of data access, ownership, copyright and licensing. This presentation gives an update on the OSGeo white paper collating and commenting the definitions proposed by different organizations by applying them to real-world use cases form the geospatial domain. We start off exploring What Open Data Really Is by looking into the definition of the terms geodata, dataset, authenticity, service, authority, public good and infrastructure. Then we look at the definition of Open Data itself which can be divided into at least two distinct categories: * Data collected and maintained by volunteer communities (for example OpenStreetMap) * Data from public administrations / government * Data from private businesses Next we will look into the definition of Open Data as proposed by relevant organizations (OSGeo, the Open Knowledge Foundation, government and commercial providers). Each of these definitions come in different tastes and with differing potential for use and derivative work depending on the underlying licensing model. In the examples we will focus on he geospatial domain and compare the ODbL as used by OSM data, CreativeCommons for OSM maps, the Open Government License of the UK, the (non-license) Public Domain as is broadly used in the USA and compare them to a variety of proprietary business models (Google, Bing, Nokia and even Facebook). In the second part we will highlight examples of how this data can be used in geospatial services - and make a distinction why services for Open Data may actually not be quite as open as the Open Data Definiton claims they should be. Finally we will highlight one product (http://SplashMaps.net) that makes exclusive use of Open Data from many different of the above mentioned resources. The SplashMaps business model (just one of many) is completely designed around Open Data requirements and communities. If there is interest we invite to a Birds of a Feather session for a dialog about the opportunities and challenges of Open Data. As a side note we describe the Open Source software stack powering the enterprise.