IN51A-1685. Current System. Thesauri “ narrower term ” relation. Selected Logical Constraints (disjointness, inverse, …). Frames (properties). Formal is-a. Catalog/ ID. Semantically Enabled Knowledge Representation of Metamorphic Petrology Data
Semantically Enabled Knowledge Representation
of Metamorphic Petrology Data
Patrick West1 (firstname.lastname@example.org), Peter Fox1(email@example.com), Frank Spear2 (firstname.lastname@example.org),
Sibel Adali3(email@example.com), Cam Le Nguyen1(firstname.lastname@example.org),
Benjamin Hallett2(email@example.com), L. K.S. Horkley2(firstname.lastname@example.org)
(1Tetherless World Constellation, Rensselaer Polytechnic Institute 110 8th St., Troy, NY, 12180 United States)
(2Earth and Environmental Science, Rensselaer Polytechnic Institute 110 8th St., Troy, NY, 12180 United States)
(3Department of Computer Science, Rensselaer Polytechnic Institute 110 8th St., Troy, NY, 12180 United States)
More and more metamorphic petrology data is being collected around the world, and is now being organized together into different virtual data portals by means of virtual organizations. For example, there is the virtual data portal Petrological Database (PetDB, http://www.petdb.org) of the Ocean Floor that is organizing scientific information about geochemical data of ocean floor igneous and metamorphic rocks; and also The Metamorphic Petrology Database (MetPetDB, http://metpetdb.rpi.edu) that is being created by a global community of metamorphic petrologists in collaboration with software engineers and data managers at Rensselaer Polytechnic Institute. The current focus is to provide the ability for scientists and researchers to register their data and search the databases for information regarding sample collections.
What we present here is the next step in evolution of the MetPetDB portal, utilizing semantically enabled features such as discovery, data casting, faceted search, knowledge representation, and linked data as well as organizing information about the community and collaboration within the virtual community itself. We take the information that is currently represented in a relational database and make it available through web services, SPARQL endpoints, semantic and triple-stores where inferencingis enabled. We will be leveraging research that has taken place in virtual observatories, such as the Virtual Solar Terrestrial Observatory (VSTO) and the Biological and Chemical Oceanography Data Management Office (BCO-DMO); vocabulary work done in various communities such as Observations and Measurements (ISO 19156), FOAF (Friend of a Friend), Bibo (Bibliography Ontology), and domain specific ontologies; enabling provenance traces of samples and subsamples using the different provenance ontologies; and providing the much needed linking of data from the various research organizations into a common, collaborative virtual observatory.
In addition to better representing and presenting the actual data, we also look to organize and represent the knowledge information and expertise behind the data. Domain experts hold a lot of knowledge in their minds, in their presentations and publications, and elsewhere. Not only is this a technical issue, this is also a social issue in that we need to be able to encourage the domain experts to share their knowledge in a way that can be searched and queried over. With this additional focus in MetPetDB the site can be used more efficiently by other domain experts, but can also be utilized by non-specialists as well in order to educate people of the importance of the work being done as well as enable future domain experts.
In the current implementation of MetPetDB we use a relational database to store data. For simple cases, the use of relational systems like this are enough. But there are more requirements being placed on systems to not only provide data, but to provide knowledge information. For this, we need a more expressive representation of the data, and the metadata, and the community of researchers within a given science domain. More and more, however, students and non-specialists (citizen scientists for example) are utilizing systems to gain access to information about the our surrounding environment.
Next Generation System
Originally from AAAI 1999- Ontologies Panel by Gruninger, Lehmann, McGuinness, Uschold, Welty;
– updated by McGuinness.
Description in: www.ksl.stanford.edu/people/dlm/papers/ontologies-come-of-age-abstract.html
Drupal shot, projects, people, organizations, bibTeX, web services, linked to PetDB, linked to document place, S2S
Modern informatics enables a new scale-free framework approach
Next Generation System
There’s not a lot of information here beyond the results of the search. If one clicks on the one of the result samples, you get the screen below with some information, but nothing that links to “knowledge information”. In other words, no links for what minerals are, or what chemical analysis were used, or who the owner is of the sample, linked data, project information, etc…
To accomplish the redevelopment of the MetPetDB portal we have decided to follow the Semantic Web Methodology and Technology Development Process, as developed by Peter Fox at Tetherless World Constellation. This methodology is an iterative approach to developing semantically-enabled knowledge information systems.
We start with face-to-face meetings with current researchers and developers, taking a look at the current portal (upper right). From there we can developing use cases from current usage models as well as future usage. We analyze the information models, develop more expressive representations of the information, review the information and iterate. Adopt technologies to implement the system and leverage existing systems. And iterate, and evolve, and iterate, and evolve.
Not only do we represent concepts, but relationships between concepts. Provides for linked data services, easier implementation of faceted browsing, metadata representation, data representation, discovery mechanisms, tying together the science domain, community domain, educational domain, provenance domain.
If you know where to look, you can click on the “Wiki” tab to get some additional information. But context is lost at that point.
Not to say that there isn’t a place for relational representation, especially it terms of using PostGIS and geographic tools.
Results and Next Steps
Stephan Zednik and Evan Patton – Tetherless World Constellation
Tetherless World Constellation, Rensselaer Polytechnic Institute
bibTeX – ontology for bibliographic data (http://zeitkunst.org/bibtex/0.1/)
CMS– Content Management System
FOAF - Friend of a Friend
MetPetDB – Metamorphic Petrology Data Base
O&M – Observations and Measurements (http://www.opengeospatial.org/standards/om)
OWL – Web Ontology Language
RDFs – Resource Description Framework Schema
RPI/TWC – Rensselaer Polytechnic Institute / Tetherless World Constellation
Scale-Free – A scale-free network is a network whose degree distribution follows a power law, at least asymptotically
SWEET – Semantic Web for Earth and Environmental Terminology (http://sweet.jpl.nasa.gov)
XSL– Extensible Stylesheet Language
VSTO – Virtual Solar Terrestrial Observatory