At the IUCN's World Conservation Congress I ran into two applications of machine learning (ML) to guard protected areas against direct detrimental human activity. Both stories are success stories but also both applications are in their early phases. In this post, I will compare the two and ask a couple of common sense questions that may be of interest for the long-term viability of the approaches.
This started as a post about particular applications of machine learning (or ML) in protected area management, but while writing the 'one paragraph' introduction into machine learning, it became two paragraphs and then some more. Then it became a post in itself. Obviously, you will find other introductions if you search for them. I suggest... Continue Reading →
Last Friday, the IUCN World Conservation Congress 2021 started. For me an excellent opportunity to learn about the state of the art of data collection in nature conservation. Let me just give a list of all the sessions that I thought would give some insight into the state of the art of digital tools, databases and methods
June 2020 At Osa Conservation (where I am currently doing volunteer work), sea turtle research has been going on for at least ten years. Data about the sea turtles, their nests and the hatchlings, is written down in note books during the beach patrols. Later, this data is collected in one or more spreadsheets. Over... Continue Reading →
In this text, I will explain the problem that the sea turtle researchers at Osa Conservation asked me to solve. It turns out that they have a data problem that I am sure many other researchers and organizations have. The solution is a database tool to stitch data from multiple tables together, while addressing differences... Continue Reading →
The choice of your research software in part depends on the structure of your data. Here, I will look at the structure of your data. Here, I will show some examples of research data and discuss which software is in my view best suitable to handle them.