DOLCE ROCKS: Integrating Geoscience Ontologies with DOLCE

2021

The Environmental and Earth sciences are faced with complex and dynamic challenges: they cannot be solved in isolation from each other or from other sciences, such as the social and health sciences. Researchers who tackle real world challenges must have data that are easy to use and understandable in a variety of contexts. An important element of understanding these data is the use of well-organised, community-accepted terminology for data. With the increasing uptake of the semantic web and the demand for open data, data descriptors of varying quality and technical maturity are proliferating (e.g. ESIP/RDA Earth, Space and Environmental Sciences Interest Group (ESES-IG), Semantic Resource Catalogue, 2021). These range from simple lists, through thesauri and taxonomies, to formalised ontologies. This proliferation can be extremely confusing for the practitioner (data creator or re-user), as there are no agreed criteria to support a selection decision. In addition, the variety of desc...

2004

Abstract In Geoscience domain, large amounts of data are accessible, however they vary in formats and are stored at various organizations leading to problems of data discovery, data interoperability and usability. In this paper, we propose a new semantic metadata paradigm based on ontologies and the use of Semantic Web languages. Our suggested data model ontology is used to guide the generation of metadata for individual datasets.

To address the environmental and economic challenges of the 21st century it is incumbent upon the global community to evolve and sustain a global observation network. These observations serve as the foundation for the models that are used to describe Earth processes and can be used to predict the effect of different forcings on the planet. As this observational data accumulates in global archives new opportunities become available for knowledge discovery about the Earth system. However, access to these observational data is optimized for the science teams for whom the instruments were launched and access by operational users may be problematic. This paper proposes the use of ontologies for semantic interoperability in archives. Semantic interoperability requires resolving various context-dependant incompatibilities where the context refers to the knowledge that is required to reason about the system for answering a specific query. Therefore, it is important to provide contextual knowledge of domain applications in order to ensure semantic interoperability. Each information source serves as a context for the interpretation of the information contained therein. Assuming that ontologies are used to capture the context of the information entities, then as we move from one context to another, there is a requirement to integrate ontologies. A hybrid ontology approach consisting of a global shared ontology that encompasses all the local application level ontologies for a domain of interest (e.g. Coastal zone hazards) is advocated in this paper.

International Conference on HydroScience …, 2004

Recent developments and discussions on nationwide scales increasingly stress the need for semantic interoperability among communities due to the lack of specific domain descriptions of the data being processed. These shortcomings are largely based on the fact that each community typically only focuses on its specific needs with little or no attention paid to making these community-specific data descriptions part of a much bigger data realm. We state that part of the problem arises because the formalizations of the available metadata schemas are general, difficult to implement and inflexible to be extended. In this paper we attempt to show that through the use of the Ontology Web Language (OWL) and the creation of domain specific ontologies some of these shortcomings can be overcome. This is demonstrated by creating two examples of knowledge inference to reason from a domain ontology. In the first one we created an ontology for the US Geological Survey Hydrologic Units, where logical inference is use to extract a list of desire watershed names that a user could select to fill a metadata element. In the second example we show the possibilities of extending a metadata element and restricting it to accept values from another distributed resource, such as the Global Change Master Directory (GCMD). We conclude that knowledge representation systems like OWL provide a more flexible platform and possibility to reuse distributed resources, simplifying the process of creating metadata schemas for the hydrologic community.

Journal of Web Semantics, 2006

Rapid advances in information technologies continue to drive a flood of data and analysis techniques in ecological and environmental sciences. Using these resources more effectively and taking advantage of associated cross-disciplinary research opportunities poses a major challenge to both scientists and information technologists. These challenges are now being addressed in projects that apply knowledge representation and Semantic Web technologies to problems in discovering and integrating ecological data and data analysis techniques. In this paper, we present an overview of the major ontological components of our project, SEEK ("Science Environment for Ecological Knowledge"). We describe the concepts and models that are represented in each, and present a discussion of potential applications of these ontologies on the Semantic Web.

2011

This paper presents our work on development of OWL-driven systems for formal representation and reasoning about terminological knowledge and facts in petrology. The long-term aim of our project is to provide solid foundations for a large-scale integration of various kinds of knowledge, including basic terms, rock classification algorithms, findings and reports. We describe three steps we have taken towards that goal here. First, we develop a semi-automated procedure for transforming a database of igneous rock samples to texts in a controlled natural language (CNL), and then a collection of OWL ontologies. Second, we create an OWL ontology of important petrology terms currently described in natural language thesauri. We describe a prototype of a tool for collecting definitions from domain experts. Third, we present an approach to formalization of current industrial standards for classification of rock samples, which requires linear equations in OWL 2. In conclusion, we discuss a range of opportunities arising from the use of semantic technologies in petrology and outline the future work in this area.

GeoLink is one of the building block projects within Earth-Cube, a major effort of the National Science Foundation to establish a next-generation knowledge infrastructure for geosciences. As part of this effort, GeoLink aims to improve data retrieval, reuse, and integration of seven geoscience data repositories through the use of ontologies. In this paper, we report on the GeoLink modular ontology, which consists of an interlinked collection of ontology design patterns engineered as the result of a collaborative modeling effort. We explain our design choices, present selected modeling details, and discuss how data integration can be achieved using the patterns while respecting the existing heterogeneity within the participating repositories.

2009

Geographical Information is increasingly captured, managed and updated by different cartographic agencies. This information presents different structures and variable levels of granularity and quality. In practice, such heterogeneity causes the building up of multiple sets of geodata with different underlying models and schemas that have different structure and semantics. Ontologies are a proposal widely used for solving heterogeneity and a way of achieving the data harmonization and integration that GIS and SDI need. This paper presents three hydrographical ontologies (which are built using topdown and bottom-up approaches) and an approach to comparing them; the goal of this approach is to prove which ontologies have a better coverage of the domain. In order to compare the resultant ontologies, six qualitative facets have been studied: sources used (amount, richness and consensus), reliability of building approaches (community extending use, recommendations), ontology richness (number and types of components), formalization (language), granularity (scale factor) and the design criteria followed.

Journal of biomedical semantics, 2016

The Environment Ontology (ENVO; http://www.environmentontology.org/ ), first described in 2013, is a resource and research target for the semantically controlled description of environmental entities. The ontology's initial aim was the representation of the biomes, environmental features, and environmental materials pertinent to genomic and microbiome-related investigations. However, the need for environmental semantics is common to a multitude of fields, and ENVO's use has steadily grown since its initial description. We have thus expanded, enhanced, and generalised the ontology to support its increasingly diverse applications. We have updated our development suite to promote expressivity, consistency, and speed: we now develop ENVO in the Web Ontology Language (OWL) and employ templating methods to accelerate class creation. We have also taken steps to better align ENVO with the Open Biological and Biomedical Ontologies (OBO) Foundry principles and interoperate with existi...