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Open source licences are great for research, study, proof of concept, method developments and many other reasons. Which one did I omit? But not for commercial use. Obviously, some consultancy services can be sold without the data or results. Below is a list of my favourite tools, data catalogues and platforms I have encountered and…
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Who does not like Google Earth Engine (GEE)? It has a neat interactive JS editor with on-the-fly visualisation, a huge open-source data library and a large set of functions and methods bridging the two. Plus, GEE is well documented. In addition, you can tap into other google cloud services for data storage, Machine Learning to…
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Environmental data always has a spatial and temporal dimension (4D). Whether it is species survey, asset inventories or maintenance checklists, the fulcrum platform has been the tool of our choice after testing similar service providers. It helps to configure data collection forms in seconds from location, images, barcode, user control, workflows, and even produce one-click…
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I am under the impression half the Medium, Reddit and Twitter crowd is asking this? Also, many software, ML-driven trading bots ask for fees that fall within 5% of the client’s portfolio. I will not go into the projects and compare outcomes and costs/fees here but just clarify a few relevant basics for decision-making. Fundamentals:…
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Binary null-hypothesis significance testing with an arbitrary P-value cutoff still is the standard way to report scientific findings due to missing alternatives. Muff et al. 2022 suggest in an #opinion in Trends in Ecology & Evolution a different language of evidence that allows for a more nuanced approach, previously been presented in medical statistics, and…