Paricia V

Paricia is a hydroclimatic data management system for collecting, managing and exploring time-series observations from environmental monitoring stations. The system was originally developed around stations in the Andes and has since been generalised to support data from locations worldwide.

The platform supports research into environmental change, the water cycle and the management of water resources. It is coordinated by Professor Wouter Buytaert in Imperial College London’s Department of Civil and Environmental Engineering, and builds on earlier work undertaken in collaboration with the Foundation for the Protection of Water (FONAG) in Quito, Ecuador.

The current engagement extended Paricia as a research data service by improving its interoperability, supporting additional routes for data ingestion and making it easier to compare observations from multiple monitoring stations.

This engagement was funded by the UK Centre for Ecology & Hydrology.

This engagement addressed several independent improvements and new functionality for Paricia, in addition to small front-end usability issues to make Paricia more intuitive, clear and efficient to use.

REST API

An authenticated REST API was implemented to enable users to upload new time-series data and download existing data. The API was documented using the OpenAPI specification, providing a clear description of its endpoints, request formats and responses. The API provides a stable integration point for external tools and services. It also establishes a foundation for future applications that may use Paricia as a back end without depending directly on its existing web interface.

ThingsBoard integration

An import workflow was added so that users can pull sensor data from a ThingsBoard instance as an alternative to uploading data manually. Users provide the ThingsBoard server URL, credentials and sensor identifier required to retrieve the data. The ThingsBoard credentials can then be retained in the user account for subsequent use. This integration reduces repetitive data-entry work and makes it easier to incorporate observations from existing Internet-of-Things deployments into Paricia’s research data-management workflow.

Multi-station comparison

The system was extended to plot traces from multiple stations simultaneously. Researchers can use this functionality to compare how measurements evolve over time at different monitoring locations. One important use case is comparing the flow of water at stations positioned along a river course. The resulting view supports exploratory analysis by making it easier to inspect temporal relationships, identify differences between sites and assess patterns before undertaking more detailed analysis or modelling.

Spatial data feasibility work

The project explored the feasibility of integrating spatial data into Paricia. This included considering how spatial information could be stored in the database, how it could be visualised and how users might interact with it. The work produced an implementation-oriented assessment and a proof-of-concept direction for future development. It also considered the views and controls likely to be required by users. This gives the research team a clearer basis for deciding how spatial capabilities should be developed in a later phase, without introducing unvalidated production features at this stage.