The demand for spatial metadata to describe spatial data is growing in the networked environment. Yet, currently metadata acquisition and management often play a subordinate role in many organizations and are considered overhead. If at all, metadata are acquired much after the spatial data and are stored in separate repositories. Consequently, there are two independent data sets to manage and update: spatial data and metadata. These are often redundant and inconsistent, as it is not always clear which information is metadata and which is spatial data.
Looking at the interoperability in Spatial Data Infrastructures (SDIs) from a technical point of view, the specialized spatial search engine needs spatial data which are labeled and indexed by metadata. The more reliable and consistent such metadata are, the better they support an SDI as an enabling platform to search, exchange and process spatial data.This leaves a gap between the status-quo of metadata and the demand for metadata which needs to be accounted for with new metadata management concepts.
Consequently, the main focus of this thesis concerns the optimization of metadata management by integrating metadata and spatial data in a common file or database. This common metadata-spatial data set can be considered to be 'comprehensive spatial data'.
The concept of metadata-spatial data Integration enables the spatial data to carry their own metadata description with them. The approach distinguishes between already existing spatial data models, which have to be extended and newly planned data mode is and sets, which can managed commonly from the beginning. The different groups of metadata which can be integrated are discussed (implicitly derivable, explicitly derivable and new metadata attributes) and the principles how these might be placed in a model (top-down and bottom-up). The three steps of Integration include firstly a semantic analysis and translation, secondly a structural analysis and thirdly hierarchical Integration as well as a semantic transformation.
Provided that common metadata-spatial data sets exist, the concept of views offers the possibility to extract metadata and spatial data according to various Standards and other excerpts from the comprehensive data set. This gains flexibility and interoperability for using common metadata-spatial data sets in an SDI environment in which different Services and users need different extracts and structures of a certain data or metadata set.
In order to review the feasibility of the concept of metadata-spatial data Integration three test data models and their data sets are integrated with their corresponding metadata. The Swiss federal cadastral model, a water supply model of the City of Zurich and an environmental data model vary in complexity, size modeling structure, modeling language as well as in the question whether they are standardized. The results of this case study show that the integration of metadata in existing models and data sets is feasible. For each of the chosen models certain top-down and bottom-up metadata attributes are defined. Furthermore, the implicitly and explicitly derivable attributes are ascertained. In a Workshop the common models were verified with experts who know the original models well.
In order to be able to use the concept of integration on any data set in a similar way, rules for the integration are necessary. Therefore, general principles are derived for object-oriented and relational modeling languages by comparing the results from the case study and abstracting them to a general case of any spatial data set. A group of general, automatic principles to insert certain metadata at a specific place in the model has been defined. These automatic principles consist of general top-down metadata that are valid for the whole model and bottom-up metadata that mirror the changes and heterogeneity of data within the model. Notwithstanding,it is also necessary for the modeling expert who knows the spatial data well to choose which metadata can be derived implicitly and explicitly.
In order to support the common management of metadata and spatial data with tools and to support new metadata-spatial data sets in their common handling, two prototype implementations are realized. The first prototype is an existing open source modeling Software called INTERLIS/UMLEditor, which is extended by implementing the principles for metadata-spatial data integration. For example, a new functionality is that certain metadata are added automatically when a new model is generated. Consequently common modeling for spatial data and metadata is supported in a harmonized way. The second prototype implementation explores the possibilities of creating views and functionalities of views in the relational database management system Oracle 9i. Views according to different profiles of
ISO 19115 are extracted from integrated data sets.