排序方式： 共有197条查询结果，搜索用时 15 毫秒
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We consider the problem of enabling interoperability and information sharing among geospatial applications that use ontologies to describe their concepts and the relationships among them. We present two fully automatic alignment methods that use the graph structures of a pair of ontologies to establish their alignment, that is, the semantic correspondences between their concepts. We have tested our methods on geospatial ontologies pertaining to wetlands and four other pairs that belong to a repository that has been used in the Ontology Alignment Evaluation Initiative (OAEI). Using these ontologies, we have compared the effectiveness (precision and recall) of our methods against the Similarity Flooding Algorithm that was proposed by others and show that for each of the tested ontologies one of our methods is at least as effective as their method. We have tuned the performance of our methods by introducing a greedy approach that reduces the number of concepts that get compared. This approach reduces runtime by approximately 30% with a minor compromise to the effectiveness of the results. To further validate our approach, we participated in the OAEI competition to align a pair of ontologies, each with a few thousand concepts. 相似文献
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The quality and integrity of spatial data is very important to support interoperability among different systems. To reach this aim integrity rules defined by the application play an important role (for example, constraints between object classes). In this article, we propose a methodology to define integrity constraints using user level spatial relations between classes of individuals. We will also provide mapping rules from user level relations to geometric level operators to allow the computation of relations. As a case study, we will define the constraints for the class of rivers and some of its specializations. 相似文献
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《地学前缘(英文版)》2023,14(2):101521
Lithofacies paleogeography is a data-intensive discipline that involves the interpretation and compilation of sedimentary facies. Traditional sedimentary facies analysis is a labor-intensive task with the added complexity of using unstructured knowledge and unstandardized terminology. Therefore, it is very difficult for beginners or non-geology scholars who lack a systematic knowledge and experience in sedimentary facies analysis. These hurdles could be partly alleviated by having a standardized, structured, and systematic knowledge base coupled with an efficient automatic machine-assisted sedimentary facies identification system. To this end, this study constructed a knowledge system for fluvial facies and carried out knowledge representation. Components include a domain knowledge graph for types of fluvial facies (meandering, braided and other fluvial depositional environments) and their characteristic features (bedforms, grain size distribution, etc.) with visualization, a method for query and retrieval on a graph database platform, a hierarchical knowledge tree-structure, a data-mining clustering algorithm for machine-analysis of publication texts, and an algorithm model for this area of sedimentary facies reasoning. The underlying sedimentary facies identification and knowledge reasoning system is based on expert experience and synthesis of publications. For testing, 17 sets literature publications data that included details of sedimentary facies data (bedforms, grain sizes, etc.) were submitted to the artificial intelligence model, then compared and validated. This testing set of automated reasoning results yielded an interpretation accuracy of about 90% relative to the published interpretations in those papers. Therefore, the model and algorithm provide an efficient and automated reasoning technology, which provides a new approach and route for the rapid and intelligent identification of other types of sedimentary facies from literature data or direct use in the field. 相似文献
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地理本体与空间信息多级网格 总被引：12，自引：0，他引：12
为解决空间数据分布异构的问题,根据地理本体与地理网格的特点,提出一种将地理本体映射到地理网格的新方法,并用该方法构造一种基于本体的空间信息网格系统。该系统通过描述空间信息的语义内涵的本体系统对空间信息数据进行索引和组织,并以地理网格为其存储和管理单元,可以有效地解决在广域网络环境下的空间信息资源整合的问题,促进空间信息共享与利用的研究。 相似文献
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地质数据本体构建及其在数据检索中的应用 总被引：1，自引：1，他引：0
针对传统以关键词、主题词等字符串匹配为核心的地质数据检索方法存在的查不全、查不准的问题,给出了基于地质数据本体的语义级检索解决方案。通过对地质数据的概念、属性、关系、规则及相应实例的详细表达,构建了地质数据本体(矿产资源预测部分),搭建数据检索系统并开展了应用实践。实验表明,引入地质数据本体后,检索结果在数据的查全率和查准率方面显著提高,并能智能推送相关联的数据信息。开发的地质大数据专题检索系统,实现了对局域网中多源异构地质数据的获取、半自动化标注和语义关联检索,满足地质大数据应用服务的需求,对于大数据时代背景下地质数据的精确发现、深层挖掘及共享有重要意义。 相似文献
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资源环境信息分类编码及其与地理本体关联的思考 总被引：19，自引：2，他引：17
通过对多年来我国资源环境信息分类编码工作经验与教训的学习与思考，对地理信息分类编码工作中应考虑的若干基本问题，在前人研究与实践的基础上，提出了一种资源环境信息分类编码的建议方案；面对正在建设和发展中的电子政务、科学数据共享和可持续发展信息共享三大系统，提出必须研究和解决三大系统中共同的基本地理信息分类和编码问题，以实现全社会的信息共享与数据交换；最后，讨论了地理信息本体的相关概念，认为采用信息本体技术进行资源环境信息分类编码是具有前瞻性的一项研究工作。 相似文献
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Monitoring soil moisture with satellite sensors is an effective approach for agricultural drought assessment. Currently, large quantities of sensor-derived observation data with different observation metadata models exist, and they require efficient and accurate methods of discovery. In this study, an earth observation (EO) metadata ontology with a spatiotemporal-spectral-enhanced structure is designed to solve this problem. The ontology is based on the proposed EO metadata model, which is composed of nonfunctional and functional sub-modules and supports the Open Geospatial Consortium EO profile of observations and measurements. Using EO metadata ontology, an application for soil moisture monitoring in Hubei Province in China is tested. The results indicate that metadata retrieval with a spatiotemporal-spectral-enhanced method can efficiently achieve fine-grained discovery of qualified EO metadata and obtain soil moisture monitoring information from sensor images. In summary, the spatiotemporal-spectral semantics in the proposed ontology demonstrate the use of EO metadata in the context of a soil moisture monitoring application, improving the efficiency and accuracy of EO metadata discovery. 相似文献