The importance of open data science tools in science: a list of references

Open data science is the combination of open science, data science, and team science. We promote and practice this with the Ocean Health Index by using software tools that make our work transparent, reproducible, and shared publicly online. These concepts are being discussed more and more in the news and in the academic literature. There are so many great articles on these topics that we have started this list, along with a quote from the article to give a sense of its content.

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Five years of global Ocean Health Index scores

Today the Ocean Health Index (OHI) announces the completion of the fifth annual global Ocean Health Index (OHI) assessment at the 17th annual Global Environment Facility Large Marine Ecosystem meeting in Paris. Global OHI scores represent ocean health for 220 coastal nations and territories and are calculated with the same methods and best available information each year. The OHI, established in 2012, is a partnership led by scientists from the National Center for Ecological Synthesis and Analysis (NCEAS) at the University of California at Santa Barbara and Conservation International.

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Resources for R and Data Science

Conducting an Ocean Health Index assessment requires collaborative coding in R, and we are often asked for the best way to learn R as well as other data science concepts and tools. There are many great resources available but here are some of the free, online resources we have found helpful:

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Colombia's Ocean Indicator Framework

Colombia was one of the first countries to begin an OHI+ assessment: they have been working for 2.5 years. Their work has already yielded positive policy and management changes.

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