FOSS4G-Asia 2024

istSOS (http://istsos.org) is a software that has been designed to support sensor data management, from collection to management and quality assessment to dissemination using OGC and ISO standard formats. Following the evolution of software libraries, hardware technologies and IoT wide adoption, istSOS has been reimplemented in its version 4: named “Things”. Taking its tradition of being a Python implementation OGC compliant it takes advantage of latest solutions to support the Sensor Things API (STA) specification.

At the end of the workshop participants will understand the principles of the istSOS4 and of the STA standard; will be able to setup an istSOS4 STA service and will learn how to interact with the service both as a consumer or producer, using supplementary interfaces or pure python code.

Modern research applies the Open Science approach that fosters the production and sharing of Open Data according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. In the geospatial context, this is generally achieved through the setup of OGC Web services that implement open standards satisfying the FAIR requirements.

Nevertheless, the requirement of Findability is not fully satisfied by these services since there’s no use of persistent identifiers and no guarantee that the same dataset used for a study can be immutably accessed in a later period. This fact hinders the replicability of research, particularly in recent years where data-driven research and technological advances have boosted frequent updates of datasets.

Here, we review needs and practices, supported by some real case examples, on frequent data or metadata updates in geo-datasets of different data types. Additionally, we assess the currently available tools that support data versioning for databases, files, and log-structured tables.

Finally, we discuss challenges and opportunities to enable geospatial web services that are fully FAIR. Achieving this would provide, due to the massive use and increasing availability of geospatial data, a significant push toward open science compliance, ultimately impacting science transparency and credibility.