Organize and Share Data

Ontologies can help organize information about a domain, either within a data system or across different data systems. Ontologies achieve this because of their basic features:

  • Ontologies provide a means for defining concepts so that they can be consistently accessed by a computer.
    • For example, MMI is developing a platforms ontology, which defines different types of oceanographic platforms and their properties (e.g., mobile or not), so that searches for data sets by platform type, or by properties of a platform, can be done automatically across data systems, regardless of the specific terminology used.
  • Ontologies provide hierarchical frameworks for organizing concepts
    • Classes, subclasses, and “is a part of” are examples of the hierarchical organizational framework provided by ontologies for concepts. In the MMI platforms ontology, the superclass concept is "Platform," with its subclass concepts, "AirAndOuterSpaceBasedPlatform," "EarthBasedPlatform," and "WaterBasedPlatform."
  • Ontologies permit the articulation and accessibility of relationships between concepts (instances) and properties.
    • These relationships can then be used automatically by computers to infer additional associations between concepts. Ontologies can automatically classify concepts according to the properties defined for those concepts. For example, a water-based sensor could be classified as a subclass of a sensor, simply if a property of the water-based sensor is also a property of a sensor. In other words, the property can be used to classify water-based sensors as a type of sensor, without having to manually create water-based sensors as a subclass of sensors.
  • Ontologies can be extended to provide any kind of relationship, or mapping, between individual terms in separate ontologies.
    • For example, at the MMI workshop, Advancing Domain Vocabularies, a sensors working group identified and mapped sensor-related terms from several vocabularies, including those from WHOI, MBARI, LDEO, SIO, TAMU, NGDC, CO-OPS, ACT, and BODC. This work was the precursor to the development of the MMI Sensor Ontology project, the goal of which is to develop a sensor ontology, based on existing vocabularies and the mappings initiated at the MMI workshop.

Through application of these features, ontologies provide a variety of higher level knowledge-management capabilities, each of which helps organize information and knowledge:

  • Ontologies provide consistency to the terms used in metadata records.
    • Consistency in metadata is essential to keeping information organized, making it discoverable, and enables interoperability between data systems.
  • Ontologies can be used to generate knowledge bases about one or more specific domains(s).
    • Each ontology represents a set of knowledge about some topic area. By connecting related ontologies, the knowledge framework can be extended to cover a wider domain.
  • Ontologies provide more powerful terms for filling out metadata records, so that they can better represent information.
    • By formally defining the terms used in metadata records, and enabling those terms to be mapped to other terms relevant to that community, ontologies extend the completeness, precision, computability, and extensibility of the metadata records. (Each term in an ontology can carry with it the context of the entire model, due to more complex semantic statements and the inference capabilities of Description Logics). For example, ontologies can define the values used to complete metadata fields like Keywords. The terms can then be mapped to other vocabularies, and interoperability is facilitated between different metadata records, regardless of the specific terminology used.
  • Ontologies support discovery and understanding through interactive navigation.
  • The relationships captured by ontologies are analogous to those in topic maps—they tie together the different terms of the ontology. Visual presentation of these relationships provides a different way to view the knowledge model represented by the ontology, and interactive tools allow it to be easily explored, often with serendipitous results. These explorations can be built into the interfaces used to discover data sets and other scientific materials, allowing searches to be qualified in ways that make sense for the particular subject domain.

Suggested Citation

Alexander, P. 2018. "Organize and Share Data." In The MMI Guides: Navigating the World of Marine Metadata. Accessed October 20, 2020.