eLTER Software workshop - Introducing new tools
This workshop will focus on several data collection, analysis and visualization tools that have been developed in the context of eLTER. The workshop is aimed at researchers, administrators and technicians who are involved in a eLTER projects, or long-term ecological research.
The programme includes technical activities, and potential participants should have a background in spatial and/or statistical software. Thus, a basic knowledge of R and python will help to get the most out of the workshop. The format for this workshop will be “hands-on”, such that each participant will learn to use all of the tools using his/her laptop. Sufficient time will be dedicated to each tool to allow participants to install software and work with the tools, and also incorporate data from their own eLTER sites. We will also visit Yzeron catchment as an example of eLTER Site.
Practical information on travel and accommodation.
This workshop might be interesting for you, if you (expand):
want to use the the analytical platform for creating workflows, apps and code (DataLabs)
want to use an R Shiny or panel interface to interact with the data (DataLabs)
want to get data out of DEIMS, e.g.
Students working with GIS data
Scientists looking for suitable sites for projects
Network managers wanting to know the status of their network
Researchers that want to analyse the existing site data
work with R for statistical and geospatial analysis in the eLTER and LTER-RI community (ReLTER):
Scientists that want to know which observed properties are available for eLTER sites, to find and download available data.
Students (Ph.D., Post doc) that want to work with these data.
eLTER site/network managers that want to obtain and analyze site information.
eLTER data managers who want to manage (upload or download), and improve or add data of their own site.
collect in situ phenological data (by phenocams/webcams or visual inspection) (PhenoApps)
The tools to be included:
1. DataLabs: A collaborative platform for scientists to share data, work, code and more.
Install relevant libraries in the notebooks (R and python) for any of the applications
DataLabs project space
Using and administering your project space
Creating project storage (NFS and object store), uploading files
Creating a Jupyter lab (the interface, terminal interface, kernels) and working collaboratively with it
Creating new Conda environments and managing packages within Conda
Create Rstudio project
manages packages within R (Packrat)
Creating DASK cluster
Start DASK cluster, access the DASK dashboard, Perform DASK calculation, Delete DASK cluster
Creating a SPARK cluster
Start SPARK session, perform SPARK calculation
Delete SPARK Cluster
Using object storage in DataLabs
Jupyter Dashboards, using Panel and Voila (Creating and using Panel and Voila sites)
Using RShiny (Setting up Rshiny sites)
Using the DataLabs catalogue
User administration tools
2. DEIMS – SDR: Dynamic Ecological Information Management System - Site and dataset registry, to discover long-term ecosystem research sites and what is measured on them.
While it is recommended to know Python, this session can be completed without knowing Python
Install pydeims on your local Python environment
Have a desktop GIS application (e.g. QGIS or ArcGIS) ready if you plan on doing a GIS exercise (see below)
General overview (scope, usage, quality assurance, basic search functionality)
GeoData Services (GIS knowledge recommended)
REST-API (basic web programming knowledge recommended)
deimsPy (basic Python knowledge is recommended)
Showing examples using datalabs
Exercise: Working with deims data (probably 2-3 different options depending on skills and interests)
Desktop GIS exercise (e.g. making maps of sites and networks using deims data) OR
Query deims using either
3. ReLTER: an R package that provides access to DEIMS-SDR, allowing it to interact with software implemented by eLTER Research Infrastructure (RI) and improving the data/information shared among the LTER network.
Install R and the ReLTER package (previous knowledge of R, while helpful, is not required)
Description about the package’s approach
Examples of different functions, including a description of the outputs of the functions
Advanced functions: interaction with remote sensing products, biodiversity repositories, data shared with DEIMS-SDR, Zenodo upload and download dataset, interaction with SOS service for download data
A mentimeter session will be proposed to collect suggestions for new functions or improvements to the package.
4. PhenoApp: a tool integrated into a set of tools (GeeLTERMap) that allows to provide an easy mapping interface from which we can visualize, analyze, download and validate Phenology metrics for any eLTER site.
Access to GeeLTERMap (through either Datalab or Google colab)
demonstration of the different available products (MODIS, S2 Phenopy NDVI, Copernicus VPP PPI)
Available metrics (SOS, EOS, LOS)
Data download for specific eLTER site
In situ data upload for eLTER sites with available historical datasets
5. Cookie cutting: A tool to harmonise official statistics and other data to eLTER site boundaries.
Existing data overview
Compatible data types