Semantic Vernacular System: an Observation-based, Community-powered, and Semantics-enabled Naming System for Organisms

Printer-friendly version


The Semantic Vernacular System is a novel naming system for creating named, machine-interpretable descriptions for groups of organisms. Unlike the traditional scientific naming system, which is based on evolutionary relationships, it emphasizes the observable features of organisms. By independently naming the descriptions composed of sets of ob- servational features, as well as maintaining connections to scientific names, it preserves the observational data used to identify organisms. The system is designed to support a peer- review mechanism for creating new names, and uses a controlled vocabulary encoded in the Web Ontology Language to represent the observational features. A prototype of the system is currently under development in collaboration with the Mushroom Observer website. It allows users to propose new names and descriptions, provide feedback on those proposals, and ulti- mately have them formally approved. This effort aims at offering the mycology community a knowledge base of fungal observational features and a tool for identifying fungal observations.


DateCreated ByLink
September 6, 2012
Han WangDownload

Related Projects:

SVF LogoSemantic Vernaculars for Fungi (SVF)
Principal Investigator: Deborah L. McGuinness
Co Investigator: Nathan Wilson
Description: Fungi are typically referred to by either scientific or common names. Neither of these terminologies meets the need for well-defined, persistent definitions of groups of fungi who exhibit similar macroscopic qualities, but may be dissimilar genetically. We propose a community-developed vocabulary that can be used to identify mushrooms based on properties that can be observed in the field (without microscopic or genomic examination). We show how an ontology can be used to develop and organize the terms and definitions and to enable applications based on the vocabulary.

Related Research Areas:

Semantic eScience
Lead Professor: Peter Fox
Science has fully entered a new mode of operation. E-science, defined as a combination of science, informatics, computer science, cyberinfrastructure and information technology is changing the way all of these disciplines do both their individual and collaborative work.
As semantic technologies have been gaining momentum in various e-Science areas (for example, W3C's new interest group for semantic web health care and life science), it is important to offer semantic-based methodologies, tools, middleware to facilitate scientific knowledge modeling, logical-based hypothesis checking, semantic data integration and application composition, integrated knowledge discovery and data analyzing for different e-Science applications.
Partially influenced by the Artificial Intelligence community, the Semantic Web researchers have largely focused on formal aspects of semantic representation languages or general-purpose semantic application development, with inadequate consideration of requirements from specific science areas. On the other hand, general science researchers are growing ever more dependent on the web, but they have no coherent agenda for exploring the emerging trends on the semantic web technologies. It urgently requires the development of a multi-disciplinary field to foster the growth and development of e-Science applications based on the semantic technologies and related knowledge-based approaches.

Concepts: eScience