Exploratory visualization of earth science data in a Semantic Web context

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Earth science data are increasingly unlocked from their local ‘safes’ and shared online with the global science community as well as the average citizen. The European Union (EU)-funded project OneGeology-Europe (1G-E, www.onegeology-europe.eu) is a typical project that promotes works in that direction. The 1G-E web portal provides easy access to distributed geological data resources across participating EU member states. Similar projects can also be found in other countries or regions, such as the geoscience information network USGIN (www.usgin.org) in United States, the groundwater information network GIN-RIES (www.gw-info.net) in Canada and the earth science infrastructure AuScope (www.auscope.org.au) in Australia. While data are increasingly made available online, we currently face a shortage of tools and services that support information and knowledge discovery with such data. One reason is that earth science data are recorded in professional language and terms, and people without background knowledge cannot understand their meanings well. The Semantic Web provides a new context to help computers as well as users to better understand meanings of data and conduct applications. In this study we aim to chain up Semantic Web technologies (e.g., vocabularies/ontologies and reasoning), data visualization (e.g., an animation underpinned by an ontology) and online earth science data (e.g., available as Web Map Service) to develop functions for information and knowledge discovery. We carried out a case study with data of the 1G-E project. We set up an ontology of geological time scale using the encoding languages of SKOS (Simple Knowledge Organization System) and OWL (Web Ontology Language) from W3C (World Wide Web Consortium, www.w3.org). Then we developed a Flash animation of geological time scale by using the ActionScript language. The animation is underpinned by the ontology and the interrelationships between concepts of geological time scale are visualized in the animation. We linked the animation and the ontology to the online geological data of 1G-E project and developed interactive applications. The animation was used to show legends of rock age layers in geological maps dynamically. In turn, these legends were used as control panels to filter out and generalize geospatial features of certain rock ages on map layers. We tested the functions with maps of various EU member states. As a part of the initial results, legends for rock age layers of EU individual national maps were generated respectively, and the functions for filtering and generalization were examined with the map of United Kingdom. Though new challenges are rising in the tests, like those caused by synonyms (e.g., ‘Lower Cambrian’ and ‘Terreneuvian’), the initial results achieved the designed goals of information and knowledge discovery by using the ontology-underpinned animation. This study shows that (1) visualization lowers the barrier of ontologies, (2) integrating ontologies and visualization adds value to online earth science data services, and (3) exploratory visualization supports the procedure of data processing as well as the display of results.


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Data Frameworks
Lead Professor: Peter Fox
Description: None.
Concepts: eScience
Data Science
Lead Professor: Peter Fox
Description: Science has fully entered a new mode of operation. Data science is advancing inductive conduct of science driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines of aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. As such it is changing the way all of these disciplines do both their individual and collaborative work.

Data science is helping scienists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.

At present, there is a lack formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience and build a skill-set.

At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.

Concepts: eScience
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
Lead Professor: Peter Fox
Description: In the last 2-3 years, Informatics has attained greater visibility across a broad range of disciplines, especially in light of great successes in bio- and biomedical-informatics and significant challenges in the explosion of data and information resources. Xinformatics is intended to provide both the common informatics knowledge as well as how it is implemented in specific disciplines, e.g. X=astro, geo, chem, etc. Informatics' theoretical basis arises from information science, cognitive science, social science, library science as well as computer science. As such, it aggregates these studies and adds both the practice of information processing, and the engineering of information systems.
Concepts: Semantic Web, eScience