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Environmental Data Training - 2022

Source for training course on environmental data analysis and processing for the XI Simbioma 2022. Each topic will have a code, data or file example, with a related video on youtube.

Table of Contents:

Environmental Data Analysis Steps (Google/Coursera)

Environmental Data Basics and Resources

  • Sources and relations
  • Time, deadline and expectation
  • Resources for environemntal information and raw data

Database, Dataset and Software

  • Database understanding and structure
  • Dataset definition
  • Software for dataset and database.
  • Relationship over data, time and space
  • SpreadSheet - Excel/Google
  • R-CRAN/R-Studio - Libraries
  • Structured Query Language (SQL) / Geography Information System (GIS) database

Dataset Setup, Clean and LOG

  • Visual validation
  • Registering changes, sources and assumptions (LOG)
  • Fields, Keys, conventions (Tidy-R)
  • Data validation
  • Qgis - Plugins, processing, add-ons, python
  • Spatial data validation (topology check)

Data collection and selection

  • Business Problem, objectives and target needs
  • Expected steps and duration
  • Data type, volume and timeframe
  • Filtering data (Spreadsheet, R-studio, SQL)
  • Data group, parts and cross relation
  • Summary and report

Hypothesis and tools

  • Initial hypothesis, problem definition
  • Graphs and charts for a start
  • Maps and tests to keep track
  • Description and explanation

Share and show

  • Analysis and pictures/images
  • Presenting results
  • Positioning, Slide usage, information transmition
  • 5 second rule
  • Highlight, focus and importance scaling
  • Dashboard, Business Inteligence, Update window

Act data-driven

  • Conclusions
  • Proposals
  • Listen and amplify
  • Correct and enhance

Open Data -Sources and formats

Scientific collection and biodiversity network

Google BigQuery

Tableau Online

Google DataStudio

Wiki constelation

GitHub / R-Markdown / Jupyter Notebooks

Qgis -Processing R

Qgis -Legend (levels, scale, constrast)

CAR/IBGE/SNUC -Brasil national spatial sources

Geobases -Espirito Santo Spatial resource

MapBiomas -Environmental historic data

Suggested Course on Spatial Data (portuguese) -SPU

Sugges 53F6 ted Course on Data Analytics (english) -Google Coursera

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