Representing and manipulating spatial data in interoperable systems and its industrial applications

Abstract

Introduction: The amount of information available nowadays is staggering and increases exponentially. Making sense of this data has become increasingly difficult because of the two factors: · The sheer volume of data · The lack of interoperability between disparate data sources and models While one can do little about the former factor, the latter one can be mitigated by advancing solutions that make data easy to work with and ensure the interoperability among data sources and models in intelligent networks. One way to achieve interoperability is to force every entity involved in the data exchange to adopt the same standard. However, organizations have heavily invested in proprietary data standards and are unlikely to replace their existing standards with a new one. Therefore, another solution is to create a standard, through which organizations can translate their data sources and share them with their customers or general community. The MIT Data Center is spearheading an initiative to create M - a language that is capable to provide the much needed interoperability between divergent data sources and models with an ultimate goal of creating a new intelligent information infrastructure (Brock, Schuster and Kutz 2006).