Getting Started with Betty's Re Search Engine
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Transcript: English(auto-generated)
00:03
Hi everyone and welcome to Betty's research engine I'm glad that you found your way to this little introduction video in this video You will learn how to get started with Betty's research engine and how it can help you accelerate your research My name is Vassily Szalbert I'm a researcher at the Institute for software and systems engineering at the TU Clausthal
00:24
And I'm looking forward to guide you through your first steps with Betty's research engine. So without further ado, let's get started Let's get started with the landing page. Most prominent here are probably the logos at the top
00:41
Note that these logos are clickable and the links will get you to websites where you can learn more about the Institute, the persona Betty or the NFDI for ink Below the logos you'll find a search bar In here you can either type in your search query directly or click on extended search to open a form which will assist you in constructing a valid GitHub search query
01:03
Next to the extended search you'll find the search button which if you were to click it now would cause a pop-up notification telling you that you first have to set your GitHub token Don't worry about that, we'll get to it in a minute At the center of the landing page you'll find a bunch of useful hypertexts
01:23
In fact one of them leads you to this video The other two will get you to our publication which I encourage you to have a look at and our GitLab On the bottom part of the page near the footer where you'll find an acknowledgement to the Germa Research Foundation is a single gear symbol If you click on it, a window will open in which you can set your tokens
01:45
Now one prerequisite for using Betty's research engine is providing a valid GitHub token This is necessary because the search process starts off by performing a search for software repositories stored on GitHub For this it uses the GitHub REST API
02:01
Entering your GitHub token might seem a little funky and is never advised to do However, rest assured, your GitHub token is safely stored in your browser and is only sent to the GitHub API We do not collect any user data Literally, we won't even know what you would be searching for Visit our publication or refer to our GitLab where we publish our code
02:25
If you want to learn more about how Betty's research engine functions If you don't have a GitHub token, you can easily create one All you need for that is a GitHub account Please refer to the GitHub documentation for that We provided you a link right here
02:41
As for the other two tokens, the Zenodo token and the OpenCitations token You don't need to set them right away However, note that you might run into rate limitations down the road The search algorithm would handle these rate limitations for you By waiting and trying again However, you would experience them as a search process taking longer
03:02
Especially if you plan to use Betty's research engine for a sequence of searches We advise you to set those tokens as well And that's it! After you set your tokens, you're good to go Alright, let's get started with your first cascading search First, I go to the gear symbol at the bottom of the page
03:23
And I paste in the GitHub token I prepared After I hit the save button I get a notification that my token has been saved successfully Nice! Now I need to type in my search query For that I choose, let's say, financial time series Since I'm interested in research-related software repository
03:41
I'm going to add a doi in readme qualifier Which basically tells GitHub that I'm only interested in software repositories Which contain a doi string in their readmes After hitting the search button I can see how the search process comes to life I can observe the amount of software repositories found on GitHub As well as the performed searches on Zenodo
04:02
Which gives me a good idea about the progress of the search This will now take a minute Alright, welcome back The search process has now finished And now we can start examining our search results As you can see, the search results are listed in this grey white table
04:22
Where you have the names of the repositories in the first column Their citation count on different platforms As well as the identified programming language of that repository Click on a specific platform to solve the results according to the citation count on that platform Or click on total citations
04:40
To sort the software repositories according to their accumulated number of citations If you click on languages You'll find a drop-down menu With all the identified programming languages As well as the number of corresponding software repositories Let's see Give me all the repositories which were written in C Nice
05:01
Now when I click on a repository name The what we call detailed view opens In the detailed view we have Of course, the link to the GitHub repository And three blue buttons If I click on show readme I get to see the repositories readme file If I click on show publications
05:20
I can see a list with all the publications that cited the software Or the paper that is associated with the software repository If I go to show details I sometimes get additional information about the repository Like in this example I get to see the abstract of the associated publication Now, let's see how we can export our search results
05:45
Alright now, let's see how we can export our search results If you want to export a single search result Click on the download button next to the repository name When you click it, you get to choose an export format I choose bibtex Because then I can import it directly
06:01
In my latte list of references Wonderful If you want to export all the search results Click on the download button next to the progress bars This time, I'll choose JSON as my preferred export format This way, I can easily import it into my, let's say, Python script
06:21
And perform my own data processing and analysis Alright folks, thank you for sticking with me to the end of this video I hope you enjoyed it If you have any feedback or experiences that you want to share with us Don't be shy, we're looking forward to it Simply write an email to the provided email address
06:41
See you next time
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