An Optimized Query Scheme for Geographic Information Data Based on Blockchain Technology

Geographic information data finds extensive applications at both the national and societal levels. The decentralized nature of blockchain technology facilitates trust among participants, eliminating the need for centralized institutions and offering a reliable database for many-to-many sharing of geographic information data. This data can be categorized into two parts: geographic data and their corresponding metadata. As of now, mainstream blockchain systems do not support the storage of excessively large data volumes on the blockchain. In contrast to the query functionality of traditional databases, existing blockchain systems are unable to directly query data fields within transactions, and their query methods are limited. This paper introduces a geographic information data query optimization solution based on blockchain technology. It involves the combined storage of both data parts using IPFS and blockchain, reducing on-chain storage redundancy, especially for metadata characteristics. Additionally, it incorporates Bloom filters and inverted index into a tamper-proof index structure, enhancing support for multi-keyword queries within the MPT tree. With this structure, users can access multiple relevant information, optimizing the query efficiency on the blockchain.