EODCtHRS Health Indicator Processing (ehipr)
The EODCtHRS Health Indicator PRocessing (ehipr) is a package developed by Harmonize Brazil Team - INPE in Python to provides a set of scripts to process the health indicator data produced by LIS to be accommodated in the EODCtHRS component. Your flow, represented in the Figure 2, starts with the step of fetching the tabular data from the bilis_harmonize github repository via API. Then, the spatial component is added to the data using the municipality grid provided by IBGE and it can be aggregated by spatial and temporal aggregation. After spatialize the data, if the user wants to crop the data to a specific region, it can be done as defining a specific parameter when call the spatialize_data function. Finally, it's possible to use the publish_data function to publish the data into GeoServer and its metadata into STAC using edpu package.
The diagram depicted in the Figure 2 contains the most important concepts behind the STAC data model:

Figure 2 - SpatioTemporal Asset Catalog Model.
The description of the concepts below are adapted from the STAC Specification:
Item: a
STAC Item
is the atomic unit of metadata in STAC, providing links to the actualassets
(including thumbnails) that they represent. It is aGeoJSON Feature
with additional fields for things like time, links to related entities and mainly to the assets. According to the specification, this is the atomic unit that describes the data to be discovered in aSTAC Catalog
orCollection
.Asset: a
spatiotemporal asset
is any file that represents information about the earth captured in a certain space and time.Catalog: provides a structure to link various
STAC Items
together or even to otherSTAC Catalogs
orCollections
.Collection: is a specialization of the
Catalog
that allows additional information about a spatiotemporal collection of data.