Galdos Systems helps organizations to develop standard consistent data models that support system integration and data sharing.
Data models describe the data flowing through the information systems that support the business processes of an organization. Data models define the conceptual, logical, and physical structures of the data used in the information systems, and should include data elements, their structure, and the relationships between them.
Data models are not absolute. Data can be modeled in many different ways, depending on what the model will be used for and the information system that it supports. Because they represent the real world, data models include representations of both concrete objects (trains, buildings, desks, lumber, cars, etc.) and abstract conceptual objects (time, delivery routes, relationships, etc.).
Galdos has extensive experience in developing open standards uses this experience to work with organizations to develop standard consistent data models. Data models that are consistent, standardized, and predictable provide the best support for managing data as a resource, and they make integrating information systems much easier. Galdos has executed data modeling projects for many different organizations around the world.
Geospatial Data Models
Galdos, with its background in developing and working with the Geography Markup Language (GML) and other data specifications, has a deep understanding of data structures. Geospatial data models are the heart of geographic information systems, and describe how the data are represented and accessed.
Geospatial data add information such as location, orientation, and geometry elements to data models. Location includes not only latitude and longitude values (or other positioning data), but also height above or below a surface. Data models need to be precise, and must explicitly define the data elements and the relationships between them for a specific domain. Data models need to allow for data interchange, and include the vocabularies and ontologies that provide meaning to the data.
Geospatial data models support GML schemas in Web Feature Services by developing data mappings, ontologies, and vocabularies. Schemas and ontologies establish common vocabularies for data sharing. GML dictionaries provide controlled vocabularies, or enumerated types, from which to select allowed values for the associated GML properties. Such enumerated types may be defined by external authorities.
Data modeling includes creating a schema mapping, from a relational schema to an XML or GML schema, and vice versa. Data models are often specified using the OMG Unified Modeling Language (UML). UML is a standardized general-purpose modeling language; a subset of UML diagrams, together with supporting documentation, provides a rich way to describe data structures.
The W3C Resource Description Framework (RDF) is a suite of recommendations that provide a standard model for data interchange on the web. RDF facilitates merging data even if the underlying schemas are different, and it provides specific support to allow schemas to evolve over time without requiring changes in the data consumers. Using RDF helps to ensure that a data model is not locked into a specific version of a schema, which would require updating whenever a new version is released.
An ontology provides a shared vocabulary for a domain or data model, describing the type of objects and/or concepts that exist, and their properties and relationships. The W3C Web Ontology Language (OWL) is designed for use by applications (machines and systems) that process information and data. OWL is a collection of languages for representing knowledge, providing semantic meaning to data, and making it easier for machines to interpret.