A New Methodology for Storing Consistent Fuzzy Geospatial Data in Big Data Environment

作     者：Khalfi, Besma de Runz, Cyril Faiz, Sami Akdag, Herman 

作者机构：Paris 8 Univ LIASD F-93526 Paris France Univ Reims CReSTIC F-51100 Reims France Pierre & Marie Curie Univ LIP6 Natl Ctr Sci Res F-75005 Paris France Tunis El Manar Univ LTSIRS Tunis 1068 Tunisia 

出 版 物：《IEEE TRANSACTIONS ON BIG DATA》 (IEEE Trans. Big Data)

年 卷 期：2021年第7卷第2期

页      面：468-482页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Fuzzy sets Geospatial analysis Big Data Data models NoSQL databases Spatial databases Fuzzy set theory Spatial databases data storage representations schema and subschema fuzzy set imprecision consistency big data NoSQL systems JSON 

摘      要：In this era of big data, as relational databases are inefficient, NoSQL databases are a workable solution for data storage. In this context, one of the key issues is the veracity and therefore the data quality. Indeed, as with classic data, geospatial big data are generally fuzzy even though they are stored as crisp data (perfect data). Hence, if data are geospatial and fuzzy, additional complexities appear because of the complex syntax and semantic features of such data. The NoSQL databases do not offer strict data consistency. Therefore, new challenges are needed to be overcome to develop efficient methods that simultaneously ensure the performance and the consistency in storing fuzzy geospatial big data. This paper presents a new methodology that tackles the storage issues and validates the fuzzy spatial entities consistency in a document-based NoSQL system. Consequently, first, to better express the structure of fuzzy geospatial data in such a system, we present a logical model called Fuzzy GeoJSON schema. Second, for consistent storage, we implement a schema-driven pipeline based on the Fuzzy GeoJSON schema and semantic constraints.