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Register a new userTowards a Modular Ontology for Space Weather Research
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Added by
Cogan Shimizu
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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The interactions between the Sun, interplanetary space, near Earth space environment, the Earths surface, and the power grid are, perhaps unsurprisingly, very complicated. The study of such requires the collaboration between many different organizations spanning the public and private sectors. Thus, an important component of studying space weather is the integration and analysis of heterogeneous information. As such, we have developed a modular ontology to drive the core of the data integration and serve the needs of a highly interdisciplinary community. This paper presents our preliminary modular ontology, for space weather research, as well as demonstrate a method for adaptation to a particular use-case, through the use of existential rules and explicit typing.
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We present an OWL 2 ontology representing the Saint Gall plan, one of the most ancient documents arrived intact to us, which describes the ideal model of a Benedictine monastic complex that inspired the design of many European monasteries.
Software engineering of modular robotic systems is a challenging task, however, verifying that the developed components all behave as they should individually and as a whole presents its own unique set of challenges. In particular, distinct components in a modular robotic system often require different verification techniques to ensure that they behave as expected. Ensuring whole system consistency when individual components are verified using a variety of techniques and formalisms is difficult. This paper discusses how to use compositional verification to integrate the various verification techniques that are applied to modular robotic software, using a First-Order Logic (FOL) contract that captures each components assumptions and guarantees. These contracts can then be used to guide the verification of the individual components, be it by testing or the use of a formal method. We provide an illustrative example of an autonomous robot used in remote inspection. We also discuss a way of defining confidence for the verification associated with each component.
In the United States, scientific research in space weather is funded by several Government Agencies including the National Science Foundation (NSF) and the National Aeronautics and Space Agency (NASA). For commercial purposes, space weather forecast is made by the Space Weather Prediction Center (SWPC) of the National Oceanic and Atmospheric Administration (NOAA). Observations come from the network of groundbased observatories funded via various sources, as well as from the instruments on spacecraft. Numerical models used in forecast are developed in the framework of individual research projects. Later, the most promising models are selected for additional testing at SWPC. In order to increase the application of models in research and education, NASA in collaboration with other agencies created Community Coordinated Modeling Center (CCMC). In mid-1990, US scientific community presented compelling evidence for developing the National Program on Space Weather, and in 1995, such program has been formally created. In 2015, the National Council on Science and Technology issued two documents: the National Space Weather Strategy [1] and the Action Plan [2]. In the near future, these two documents will define the development of Space Weather research and forecasting activity in USA. Both documents emphasize the need for close international collaboration in area of space weather.
Biomedical researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability. However, the number, variety and complexity of current biomedical ontologies make it cumbersome for researchers to determine which ones to reuse for their specific needs. To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms. We developed a new version of the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a new recommendation approach that evaluates the relevance of an ontology to biomedical text data according to four criteria: (1) the extent to which the ontology covers the input data; (2) the acceptance of the ontology in the biomedical community; (3) the level of detail of the ontology classes that cover the input data; and (4) the specialization of the ontology to the domain of the input data. Our evaluation shows that the enhanced recommender provides higher quality suggestions than the original approach, providing better coverage of the input data, more detailed information about their concepts, increased specialization for the domain of the input data, and greater acceptance and use in the community. In addition, it provides users with more explanatory information, along with suggestions of not only individual ontologies but also groups of ontologies. It also can be customized to fit the needs of different scenarios. Ontology Recommender 2.0 combines the strengths of its predecessor with a range of adjustments and new features that improve its reliability and usefulness. Ontology Recommender 2.0 recommends over 500 biomedical ontologies from the NCBO BioPortal platform, where it is openly available.
The field of Materials Science is concerned with, e.g., properties and performance of materials. An important class of materials are crystalline materials that usually contain ``dislocations -- a line-like defect type. Dislocation decisively determine many important materials properties. Over the past decades, significant effort was put into understanding dislocation behavior across different length scales both with experimental characterization techniques as well as with simulations. However, for describing such dislocation structures there is still a lack of a common standard to represent and to connect dislocation domain knowledge across different but related communities. An ontology offers a common foundation to enable knowledge representation and data interoperability, which are important components to establish a ``digital twin. This paper outlines the first steps towards the design of an ontology in the dislocation domain and shows a connection with the already existing ontologies in the materials science and engineering domain.
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