Ontology-aided annotation, visualization, and generalization of geological time-scale information from online geological map services

Abstract

Geological maps are increasingly published and shared online, whereas tools and services supporting information retrieval and knowledge discovery are underdeveloped. In this study, we developed an ontology of geological time scale by using a Resource Description Framework model to represent the ordinal hierarchical structure of the geological time scale and to encode collected annotations of geological time scale concepts. We also developed an animated graphical view of the developed ontology, and functions for interactions between the ontology, the animation and online geological maps published as layers of OGC Web Map Service. The featured functions include automatic annotations for geological time concepts recognized from a geological map, changing layouts in the animation to highlight a concept, showing legends of geological time contents in an online map with the animation, and filtering out and generalizing geological time features in an online map by operating the map legend shown in the animation. We set up a pilot system and carried out a user survey to test and evaluate the usability and usefulness of the developed ontology, animation and interactive functions. Results of the pilot system and the user survey demonstrate that our works enhance features of online geological map services and they are helpful for users to understand and to explore geological time contents and features, respectively, of a geological map.

Introduction

Cyber-infrastructure enables faster and easier creation, storage, and transfer of data, yet services facilitating efficient information retrieval and knowledge discovery are still underdeveloped (Hey and Trefethen, 2005, Stafford, 2010). In the field of geology, it has been extensively discussed that a geoscience cyber environment includes not only digitized geological data but also expertise and tools that support the transformation of data into knowledge (Brodaric and Gahegan, 2006, Howard et al., 2009, Loudon, 2009, McGuinness et al., 2009). Such expertise and tools are useful for studies of geology within a cyber environment and, more importantly, they provide support for addressing geology-related societal challenges, such as resources exploration, urban development and hazards mitigation, in the context of the cyber-infrastructure (Broome, 2005, OneGeology-Europe Consortium, 2010, Sinha et al., 2010).

Ontologies, as shared conceptualizations of domain knowledge (Gruber, 1995, Guarino, 1997), can help to improve the interoperability of geological data and facilitate the transformation of geological data into geological knowledge in the cyber-infrastructure (Brodaric and Gahegan, 2006, Galton, 2009, Loudon, 2000, Reitsma et al., 2009). There are several forms of geological ontology with varying semantic richness (i.e., precision of meanings of concepts and relationships between concepts). Following a general direction from informal to formal semantics, geological ontologies include controlled vocabularies (e.g., Bibby, 2006, Ma et al., 2010, Richard and Soller, 2008), conceptual schemas (e.g., Brodaric, 2004, NADM Steering Committee, 2004, Richard, 2006) and RDF¹ /OWL² -based ontologies (e.g., Ludäscher et al., 2003, Raskin and Pan, 2005, Tripathi and Babaie, 2008), etc.

In several recent projects, ontologies have been applied to provide featured functions in geospatial data infrastructures, thereby promoting geological data and tools that support information retrieval and knowledge discovery. In the GEON project,³ ontologies were used to mediate conceptual schemas of heterogeneous geological maps and enable semantic integration (Baru et al., 2009, Ludäscher et al., 2003). The AuScope project⁴ built vocabulary-based services for querying geological maps, which overcame differences in geoscience terms due to language, spelling, synonyms, and local variations and, thus, helped users to find desired information (Woodcock et al., 2010). The OneGeology (1G) project⁵ promoted the GeoSciML (Sen and Duffy, 2005) as a common conceptual schema, which improved the interoperability of online geological maps distributed globally (Jackson, 2007). GeoSciML was also applied in the OneGeology-Europe (1G-E) project⁶ and, compared to the 1G, the 1G-E extended vocabulary-based services and enabled multilingual annotation and translation of geological map contents among 18 Europeans languages (Laxton et al., 2010).

Through these projects, substantial developments have been made in conceptualizing geological knowledge into ontologies and using defined ontologies to mediate and/or integrate heterogeneous geological data. However, services using ontologies to support the interpretation of geological data are still underdeveloped. Provision of those services is necessary, nevertheless, because they are vital for comprehending the usability (i.e., as an essential part of interoperability (Bishr, 1998; Harvey et al., 1999)) of geological data served in a data infrastructure. Services using ontologies enable users, especially those who are not familiar with geology, not only to find desired data but also to understand and use the data appropriately (cf. Bond et al., 2007, Broome, 2005, Gahegan et al., 2009).

In the present study, an ontology of geological time scale is applied to support annotation, visualization, filtration, and generalization of geological time scale (GTS) information from online geological map services. The present study aimed to (1) show methods of using proper datatype and object properties to represent the structure of a domain (i.e., GTS) in geosciences; (2) develop functions of ontology-based annotation and visualization to help users to understand GTS contents of online geological maps; (3) develop ontology-based interactive functions to help users retrieve GTS information and discover GTS knowledge in online geological maps; and, as a whole, (4) show a novel way of using ontologies to improve geological data interoperability and facilitate geological knowledge discovery in the context of the Semantic Web.