Multidimensional and quantitative interlinking approach for Linked Geospatial Data
Linked Data is known as one of the best solutions for multisource and heterogeneous web data integration and discovery in this era of Big Data. However, data interlinking, which is the most valuable contribution of Linked Data, remains incomplete and inaccurate. This study proposes a multidimensiona...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2017-09-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17538947.2016.1266041 |
| _version_ | 1797678608488071168 |
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| author | Yunqiang Zhu A-Xing Zhu Jia Song Jie Yang Min Feng Kai Sun Jingqu Zhang Zhiwei Hou Hongwei Zhao |
| author_facet | Yunqiang Zhu A-Xing Zhu Jia Song Jie Yang Min Feng Kai Sun Jingqu Zhang Zhiwei Hou Hongwei Zhao |
| author_sort | Yunqiang Zhu |
| collection | DOAJ |
| description | Linked Data is known as one of the best solutions for multisource and heterogeneous web data integration and discovery in this era of Big Data. However, data interlinking, which is the most valuable contribution of Linked Data, remains incomplete and inaccurate. This study proposes a multidimensional and quantitative interlinking approach for Linked Data in the geospatial domain. According to the characteristics and roles of geospatial data in data discovery, eight elementary data characteristics are adopted as data interlinking types. These elementary characteristics are further combined to form compound and overall data interlinking types. Each data interlinking type possesses one specific predicate to indicate the actual relationship of Linked Data and uses data similarity to represent the correlation degree quantitatively. Therefore, geospatial data interlinking can be expressed by a directed edge associated with a relation predicate and a similarity value. The approach transforms existing simple and qualitative geospatial data interlinking into complete and quantitative interlinking and promotes the establishment of high-quality and trusted Linked Geospatial Data. The approach is applied to build data intra-links in the Chinese National Earth System Scientific Data Sharing Network (NSTI-GEO) and data -links in NSTI-GEO with the Chinese Meteorological Data Network and National Population and Health Scientific Data Sharing Platform. |
| first_indexed | 2024-03-11T23:02:22Z |
| format | Article |
| id | doaj.art-34d8e2350682494e9107db4d5f08216b |
| institution | Directory Open Access Journal |
| issn | 1753-8947 1753-8955 |
| language | English |
| last_indexed | 2024-03-11T23:02:22Z |
| publishDate | 2017-09-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj.art-34d8e2350682494e9107db4d5f08216b2023-09-21T14:38:05ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552017-09-0110992394310.1080/17538947.2016.12660411266041Multidimensional and quantitative interlinking approach for Linked Geospatial DataYunqiang Zhu0A-Xing Zhu1Jia Song2Jie Yang3Min Feng4Kai Sun5Jingqu Zhang6Zhiwei Hou7Hongwei Zhao8State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesUniversity of MarylandState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesSouth China Normal UniversityState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesLinked Data is known as one of the best solutions for multisource and heterogeneous web data integration and discovery in this era of Big Data. However, data interlinking, which is the most valuable contribution of Linked Data, remains incomplete and inaccurate. This study proposes a multidimensional and quantitative interlinking approach for Linked Data in the geospatial domain. According to the characteristics and roles of geospatial data in data discovery, eight elementary data characteristics are adopted as data interlinking types. These elementary characteristics are further combined to form compound and overall data interlinking types. Each data interlinking type possesses one specific predicate to indicate the actual relationship of Linked Data and uses data similarity to represent the correlation degree quantitatively. Therefore, geospatial data interlinking can be expressed by a directed edge associated with a relation predicate and a similarity value. The approach transforms existing simple and qualitative geospatial data interlinking into complete and quantitative interlinking and promotes the establishment of high-quality and trusted Linked Geospatial Data. The approach is applied to build data intra-links in the Chinese National Earth System Scientific Data Sharing Network (NSTI-GEO) and data -links in NSTI-GEO with the Chinese Meteorological Data Network and National Population and Health Scientific Data Sharing Platform.http://dx.doi.org/10.1080/17538947.2016.1266041geospatial datalinked datainterlinking typelink predicatedata similarity |
| spellingShingle | Yunqiang Zhu A-Xing Zhu Jia Song Jie Yang Min Feng Kai Sun Jingqu Zhang Zhiwei Hou Hongwei Zhao Multidimensional and quantitative interlinking approach for Linked Geospatial Data International Journal of Digital Earth geospatial data linked data interlinking type link predicate data similarity |
| title | Multidimensional and quantitative interlinking approach for Linked Geospatial Data |
| title_full | Multidimensional and quantitative interlinking approach for Linked Geospatial Data |
| title_fullStr | Multidimensional and quantitative interlinking approach for Linked Geospatial Data |
| title_full_unstemmed | Multidimensional and quantitative interlinking approach for Linked Geospatial Data |
| title_short | Multidimensional and quantitative interlinking approach for Linked Geospatial Data |
| title_sort | multidimensional and quantitative interlinking approach for linked geospatial data |
| topic | geospatial data linked data interlinking type link predicate data similarity |
| url | http://dx.doi.org/10.1080/17538947.2016.1266041 |
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