The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-4/W1-2022
https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-89-2022
https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-89-2022
05 Aug 2022
 | 05 Aug 2022

COLLABORATIVE VALIDATION OF USER-CONTRIBUTED DATA USING A GEOSPATIAL BLOCKCHAIN APPROACH: THE SIMILE CASE STUDY

J. R. Cedeno Jimenez, A. Folini, and M. A. Brovelli

Keywords: Citizen Science, Blockchain, Geospatial, Smart Contracts, Environmental

Abstract. Internet decentralization nowadays represents a critical topic to be addressed. It protects the users’ privacy, promotes data ownership, eliminates single points of failure and data censorship. An element that has an important role in decentralization is blockchain technology. Although blockchain has revolutionised sectors like the financial one with Bitcoin, there are still some fields where it needs to be further developed. One of these is geospatial data sharing and citizen science, where features like decentralization, immutability and transparency are needed. This study focuses on the description of a decentralized application developed specifically for geospatial data-point sharing and validation. As an example, the Informative System for the Integrated Monitoring of Insubric Lakes and their Ecosystems (SIMILE) is used. This application is developed in the Velas blockchain infrastructure and implements a combination of a Discrete Global Grid System (DGGS) with smart contracts. Two types of smart contracts were created, a cell and a registry smart contract. The cell smart contracts are individual for each DGGS partition and contain the list of observations present in a specific area. The registry smart contracts keep track of all the DGGS cells added to the system. Currently, SIMILE observations are validated by public authorities, which requires time that is not always available. Therefore, a fully working prototype was developed to solve this. Here users can add and manage personal observations and validate the ones belonging to other users. This work demonstrates the feasibility of creating decentralized applications for geographical data validation as a citizen science solution.