I have geometricly conneted time series data, for example energy usage and daylight levels, that I would like do distribute using Speckle and wonder if there is any way to do this? Right now the data is stored in CSV and h5-files.
I’m unfamiliar with h5-files; can you describe that a little more?
There is no restriction over what data types can be stored in Speckle; there are those we create for Connectivity reasons based on the Objects Kit, but anything CSV could be published to and consumed from with the Excel connector.
If the H5 files are something different, there may be a library for Python or C# that you could leverage Jupyter or Polyglot notebooks to publish to Speckle. If it is more of a binary type then we have a blob storage API that can return a storage ID you could associate to the CSV data.
If the hope is to consume this in desktop applications then it is a different prospect. What do you want to do with the data stored? Visualisation online, version control, drive automation or use Speckle Server as a data storage layer.