└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # Environmental Data Science 2 | Welcome! 3 | 4 | This repository gathers information about Environmental Data Science, such as events, groups, books, papers, journals, courses, etc. 5 | 6 | The idea is to have a place to find information about environmental data science and share it with others. 7 | 8 | Feel free to contribute by suggesting contents (e.g., [open an issue](https://github.com/beatrizmilz/Environmental-Data-Science/issues)) or by making a pull request to [add new content in this file](https://github.com/beatrizmilz/Environmental-Data-Science/blob/main/README.Rmd). 9 | 10 | This repository was created by [Beatriz Milz](https://beamilz.com/) in March 2021. 11 | 12 | # Content 13 | 14 | ## Organizations 15 | 16 | - [Openscapes](https://openscapes.org/) 17 | - [Open educational resources for Openscapes Champions](https://openscapes.github.io/series/) 18 | - [NASA Openscapes](https://nasa-openscapes.github.io/) 19 | 20 | ## Events 21 | 22 | ### Future events 23 | 24 | - [Environmental Data Science Summit - February 4 - 6, 2025 - Santa Barbara, California](https://www.nceas.ucsb.edu/environmental-data-science-summit) 25 | 26 | ### Past events 27 | 28 | 29 | - [Environmental Data Science Summit - February 6 - 8, 2024 - Santa Barbara, California](https://www.nceas.ucsb.edu/environmental-data-science-summit) 30 | 31 | - [Environmental Data Science Summit - February 7 & 8, 2023 - Santa Barbara, California](https://eds-summit.github.io/) 32 | 33 | - [Environmental Data Science Summit - February 8-9, 2022 \| Santa Barbara, California](https://eds-summit.github.io/) 34 | 35 | - [TAI4ES 2022 Summer School](https://www2.cisl.ucar.edu/events/tai4es-2022-summer-school) 36 | 37 | ## Groups 38 | 39 | - [EcoDataScience](https://eco-data-science.github.io/) - [GitHub](https://github.com/eco-data-science), [Slack](https://join.slack.com/t/ecodatascience/shared_invite/enQtNTE1MjAxMTU2NjQwLTZmYjQ5OGIyNjM0YTM4ZDhiMTA2Njc1Mjg2YjFlYWEwZDhlNjJmMTE3MzI2ZmM4ZTJhYTczNmZhYjk3YTI5NjU) 40 | 41 | ## Books 42 | 43 | - [Environmental Data Analysis - An Introduction with Examples in R](https://link.springer.com/book/10.1007/978-3-030-55020-2), by Carsten Dormann 44 | 45 | - [Introduction to Environmental Data Science](https://bookdown.org/igisc/EnvDataSci/), by Jerry Davis (SFSU Institute for Geographic Information Science) - 46 | 47 | - [Environmental Data Analysis - Methods and Applications](https://www.degruyter.com/document/doi/10.1515/9783111012681/html?lang=en), by Zhihua Zhang. 48 | 49 | - [Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences](https://onlinelibrary.wiley.com/doi/book/10.1002/9781119646181), by Gustau Camps-Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein. 50 | 51 | - [Análises Ecológicas no R](https://analises-ecologicas.com/), by FR Da Silva, T Gonçalves-Souza, GB Paterno, DB Provete, MH Vancine (in portuguese) 52 | 53 | ## Blogs and Newsletters 54 | 55 | - [Dynamic Ecology](https://dynamicecology.wordpress.com/) 56 | 57 | - [Theoretical Ecology](https://theoreticalecology.wordpress.com/) 58 | 59 | - [Methods in Ecology & Evolution - Blog](https://methodsblog.com/) 60 | 61 | ## Articles 62 | 63 | ### About Data Science 64 | 65 | - [50 years of Data Science](https://www.tandfonline.com/doi/full/10.1080/10618600.2017.1384734) - David Donoho 66 | 67 | ### About Environmental Data Science 68 | 69 | - [Data Science of the Natural Environment: A Research Roadmap](https://doi.org/10.3389/fenvs.2019.00121) 70 | 71 | - [Data Analytics for Environmental Science and Engineering Research](https://doi.org/10.1021/acs.est.1c01026) 72 | 73 | - [Machine Learning and Data Analytics for Environmental Science: A Review, Prospects and Challenges](https://iopscience.iop.org/article/10.1088/1757-899X/955/1/012107/meta) 74 | 75 | - [Evolution of machine learning in environmental science — A perspective](https://doi.org/10.1017/eds.2022.2) 76 | 77 | - [Why we need to focus on developing ethical, responsible, and trustworthy artificial intelligence approaches for environmental science](https://doi.org/10.1017/eds.2022.5) 78 | 79 | - [Machine learning and deep learning—A review for ecologists](https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.14061) 80 | 81 | - [Welcoming More Participation in Open Data Science for the Oceans](https://doi.org/10.1146/annurev-marine-041723-094741) 82 | 83 | ## Special issues 84 | 85 | - [Environmetrics - Special Issue: Environmental Data Science: Part 1 - February 2023](https://onlinelibrary.wiley.com/toc/1099095x/2023/34/1) 86 | 87 | - [Environmetrics - Special Issue: Environmental Data Science: Part 2 - March 2023](https://onlinelibrary.wiley.com/toc/1099095x/2023/34/2) 88 | 89 | - [Methods in Ecology and Evolution - Special Feature: Realising the Promise of Large Data and Complex Models](https://besjournals.onlinelibrary.wiley.com/toc/2041210x/2023/14/1) 90 | 91 | 92 | ## Journals 93 | 94 | - [Environmental Data Science - ISSN 2634-4602](https://www.cambridge.org/core/journals/environmental-data-science) 95 | 96 | - [Environmental Science and Technology](https://pubs.acs.org/journal/esthag) 97 | 98 | - [Frontiers in Environmental Science](https://www.frontiersin.org/journals/environmental-science) 99 | 100 | - [Environmetrics](https://onlinelibrary.wiley.com/toc/1099095x/current) 101 | 102 | - [Methods in Ecology and Evolution](https://besjournals.onlinelibrary.wiley.com/journal/2041210X) 103 | 104 | 105 | ## R Packages 106 | 107 | - [CRAN Task View: Analysis of Ecological and Environmental Data](https://cran.r-project.org/web/views/Environmetrics.html) 108 | 109 | ## Environmental Data Journalism 110 | 111 | - [New Data Tools and Tips for Investigating Climate Change](https://gijn.org/stories/new-data-tools-and-tips-for-investigating-climate-change/) 112 | 113 | - [Journalists Toolbox - Environment Resources](https://www.journaliststoolbox.org/2023/05/25/miscellaneous_environment_sites/) 114 | 115 | ## Data visualizations 116 | 117 | - [water data visualizations - USGS](https://labs.waterdata.usgs.gov/visualizations/index.html) 118 | - [USGS - Water Data For The Nation Blog](https://waterdata.usgs.gov/blog/) 119 | 120 | ## Workshops 121 | 122 | - [Environmental Data Visualization Literacy Workshop With R](https://www.library.upenn.edu/rdds/work/r-data-visualization-workshop) 123 | 124 | ## Courses 125 | 126 | ### Free courses 127 | 128 | - [Data Science for Ecologists and Environmental Scientists](https://ourcodingclub.github.io/course) 129 | 130 | - [Data Carpentry Ecology Curriculum](https://datacarpentry.org/lessons/#ecology-workshop) 131 | 132 | ### Disciplinas de pós-graduação no Brasil 133 | 134 | - [PRPG CIAMB - UFG](https://ciamb.prpg.ufg.br/) - [Análise de Dados Ambientais](https://files.cercomp.ufg.br/weby/up/104/o/An%C3%A1lise_de_Dados_Ambientais.pdf) - [Material da disciplina](https://lhmet.github.io/adar-ebook/) 135 | 136 | ### Academic courses 137 | 138 | - [University of California, Santa Barbara - Bren School of Environmental Science & Management - Master of Environmental Data Science](https://bren.ucsb.edu/masters-programs/master-environmental-data-science) 139 | 140 | - [Imperial College London - Msc Environmental Data Science and Machine Learning](https://www.imperial.ac.uk/study/pg/earth-science/environmental-data-science-machine-learning/) 141 | 142 | - [WEC-33806 - Data Science for Ecology - Wageningen University & Research](https://wec.wur.nl/dse/) (online course) 143 | 144 | ### Content from courses at the Master of Environmental Data Science (MEDS) - Bren School 145 | 146 | - [Reference](https://my.sa.ucsb.edu/catalog/Current/CollegesDepartments/bren/Index.aspx?DeptTab=Graduate) 147 | 148 | - [About MEDS](https://ucsb-meds.github.io/) 149 | 150 | - [All courses](https://ucsb-meds.github.io/courses.html) 151 | 152 | - [EDS 211 Team Science, Collaborative Analysis and Project 153 | Management](https://bbest.github.io/eds211-team/) 154 | 155 | - [EDS 212 Essential Math for Environmental Data 156 | Science](https://allisonhorst.github.io/EDS_212_essential-math/) 157 | 158 | - [EDS 213 Metadata Standards, Data Modeling and Data 159 | Semantics](https://brunj7.github.io/EDS-213-metadata/) 160 | 161 | - [EDS 214 Analytical Workflows and Scientific 162 | Reproducibility](https://brunj7.github.io/EDS-214-analytical-workflows/) 163 | 164 | - [EDS 215 Introduction to Data Storage and 165 | Management](https://jamesfrew.github.io/EDS_215_data_management/) 166 | 167 | - [EDS 216 Meta-analysis and Systematic 168 | Reviews](https://ucsbhydro.github.io/EDS_216_meta-analysis/) 169 | 170 | - [EDS 220 Remote Sensing and Environmental 171 | Data](https://samanthastevenson.github.io/EDS220_site/) 172 | 173 | - [EDS 221 Scientific Programming 174 | Essentials](https://allisonhorst.github.io/EDS_221_programming-essentials/) 175 | 176 | - [EDS 222 Statistics for Environmental Data 177 | Science](https://tcarleton.github.io/EDS-222-stats/) 178 | 179 | - [EDS 223 Spatial Analysis for Environmental Data 180 | Science](https://jamesfrew.github.io/EDS_223_spatial_analysis/) 181 | 182 | - [EDS 230 Modeling Environmental 183 | Systems](https://naomitague.github.io/ESM232_course/) 184 | 185 | - [EDS 231 Text and Sentiment Analysis for Environmental 186 | Problems](https://maro406.github.io/EDS_231-text-sentiment/) 187 | 188 | - [EDS 232 Machine Learning in Environmental 189 | Science](https://bbest.github.io/eds232-ml/) 190 | 191 | - [EDS 240 Data Visualization and 192 | Communication](https://bren.ucsb.edu/courses/eds-240) 193 | 194 | - [EDS 241 Environmental Policy 195 | Evaluation](https://bren.ucsb.edu/courses/eds-241) 196 | 197 | - [EDS 242 Ethics and Bias in Environmental Data 198 | Science](https://bren.ucsb.edu/courses/eds-242) 199 | 200 | ## Other 201 | 202 | - [Publications from AI2ES](https://www.ai2es.org/publications/) 203 | 204 | - [Better Science in Less time](http://ohi-science.org/betterscienceinlesstime/our_story.html) 205 | 206 | # Contributing 207 | 208 | Contributions are welcome! Please submit a pull request or open an issue to discuss a new resource. 209 | 210 | We follow this [code of conduct](https://www.contributor-covenant.org/version/2/1/code_of_conduct/) for contributors. 211 | 212 | Contributors: Beatriz Milz, Maurício Vancine, Juliano Van Melis 213 | --------------------------------------------------------------------------------