Foxit.PhantomPDF.Business.v7.3.6.321.Multilingual…Patch.-.{Core-X} ⭕
Foxit.PhantomPDF.Business.v7.3.6.321.Multilingual…Patch.-.{Core-X} ⭕
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Foxit.PhantomPDF.Business.v7.3.6.321.Multilingual…Patch.-.{Core-X}
Large database of work related activities such as tasks, assignments, homework, personal projects. I was able to use the tutorial from “0 to 60 in 60 seconds”, to build a function to make a word list in VBA. It took a while to figure out how to convert the HTML to the data I needed in a VBA array, but eventually I was able to make a word list. Great reference and tutorials for VBA development.While developing a meta-analyst for zenodo we stumbled upon a problem which seemed to be one of its most severe weaknesses. What we would like to see is a tagging of datasets to categories like
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so that we can filter our “instant search” to this subset as efficiently as possible. This approach was not entirely successful, partly because we didn’t need this feature and because it would require the authors of existing datasets (or zenodo) to manually assign the datasets to these categories and that does not sound viable.
What we did was: (1) creating the meta-analyst, (2) importing the data from zenodo and (3) defining the categories (in our case ‘experiments’) on the fly.
Step 1: Create the meta-analyst
Step 2: Importing the data
For this particular use case, we figured that we don’t need an external source for the data itself. We only need the information about it (so a link to the web-page where it can be downloaded or a reference in the dataset meta-data).
To achieve this we defined the data source as a class annotated by the type attribute of the dataset meta-data in zenodo. In our case, we know that most datasets will be ‘experimental’. Also, since we are building a meta-analyst for zenodo, we will be working with experimental datasets. Thus, we defined the data source class as:
We then needed to create an instance of this class. To do so, we opened a zenodo session and, using the menu bar (‘Plugins’ > ‘Meta-analyst’ > ‘Analyze’ > ‘Export’), got a list of datasets and chose one (‘experimental’ in our case). In the ‘Analyze’ window
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