In this page, we introduce the Extracted Features functionality (currently under beta release) that has recently been developed by the HathiTrust Research Center (HTRC). This functionality is one of the ways in which users of HTRC's tools can perform non-consumptive analysis of subsets of the HathiTrust Digital Library's corpus, that they have custom-selected by means of the workset mechanism available through the HTRC.
Currently, this functionality is available only for the HathiTrust Digital Library's public domain corpus, consisting of slightly less than 5 million volumes.
Create your workset
This section shows you how to create a custom workset, for the volume(s) contained in which you will eventually download the corresponding advanced and basic EF data files. Your workset can contain as many volumes as you wish. However, the example workset for this section will consist, for the sake of simplicity, of a single volume from the HathiTrust Digital Library's public domain collection: a published-in-1920 edition of the book of poems titled Buch der Lieder by the German poet Heinrich Heine. Then we show you how you can download the EF data files corresponding to this workset. (One of the use cases for the EF approach to non-consumptive text analysis that we have posted also uses this particular book by Heine to make its point.)
1.1 Navigate to the Portal (https://analytics.hathitrust.org/)
Navigate to the HTRC Portal. Click on the link stating “Sign In” at the upper right corner of the screen.
1.2 Sign in to HTRC Portal
After Step 1, you will reach the screen shown below. Enter your HTRC username and password at the respective fields, and then click on the “Sign In” button.
1.3 Verify that you are logged in to the HTRC Portal
After Step 2, you will arrive at the screen shown below. Verify that your HTRC username appears at the upper right corner, showing that you are successfully logged in to the HTRC Portal.
1.4 Prepare to create a workset
In this step-by-step instruction set, we will show you how to create a new workset using the HTRC Workset Builder. You will be performing a search on the HathiTrust Digital Library’s collection and then selecting some or all of the search results to constitute your workset. For simplicity, we will show you how to create a simple workset consisting of a single volume, for which you will eventually be able to download the basic and advanced feature data files, by the end of these instructions.
Other ways of creating worksets, or of making use of public worksets created by other users, also exist. For example, if you already have a comma-separated values (CSV) file that specifies the list of HathiTrust volumeIDs corresponding to the volumes that you want your workset to comprise, you can simply upload it using the "Upload workset" link. For more information about creating, uploading and browsing worksets, you can consult the instructions available at the HTRC Wiki.
Click on 'Create Workset'.
1.5 Access the HTRC Workset Builder
You should now be at the screen shown below. Click on the “More options” link.
1.6 Prepare to search the HathiTrust Digital Library
You should now be at the screen shown below. Enter Buch der Lieder in the ‘Title’ field, Heine in the ‘Author’ field and 1920 in the ‘Publish Date’ field as shown below. Then click the “Search” button.
1.7 Select specific volume(s) from the search results
Select the first of the three volumes that show up, by clicking the checkbox next to ‘Select’, as shown below.
1.8 Prepare to view the selected volume(s)
Click on “Selected Items” from among the options at the upper right corner of the screen (as shown below).
1.9 Prepare to create a workset consisting of the selected volume(s)
The volume you selected now shows up as a selected item, as shown below. Click on the “Create/Update Workset” link that is within the grey area.
1.10 Name and describe the workset that is about to be created
Enter a name (for example, 'HeinePoetry') in the ‘Name:’ field as shown below. Enter a description in the ‘Description:’ field and set the availability to ‘Private’ or ‘Public’ as you prefer. Then click on the ‘Create’ button.
1.11 Verify that the workset has been created
You should see a message, as shown below, stating that the workset has been created.
Generate and execute the data file transfer script
2.1 Return to the HTRC Portal screen
Click on the ‘Portal’ link, which is at the top right corner of the screen.
2.1 Prepare to execute an algorithm
You should now be back at the HTRC Portal screen, as shown below. Click on the 'Algorithms' link, which is near the top of the screen.
2.2 Prepare to execute the EF_Rsync_Script_Generator algorithm
From the list of algorithms that shows up, click on EF_Rsync_Script_Generator. This is the algorithm for generating the script for downloading the feature data files that correspond to your workset.
2.3 Execute the EF_Rsync_Script_Generator algorithm
Specify a job name of your choosing. You also have to select a workset that the EF_Rsync_Script_Generator algorithm will run against: Check the button saying “Select a workset from my worksets” and select your desired workset. Your screen should now look like the figure below. At this point, click the ‘Submit’ button.
2.4 Check the status of the EF_Rsync_Script_Generator algorithm's execution
You can now see the status of the job, as shown below. The status of the job will initially show as “Staging”. (Refresh the screen after some time and you will see the status to have changed to “Queued”. )
2.5 Open the completed job
Eventually, the job will have “completed”, and the screen, on refreshing, will look as follows. Click on the link representing the job name.
2.6 Prepare to download the results returned by the EF_Rsync_Script_Generator algorithm
At this time, the screen should look like the following:
At the very bottom left of your browser window, you will see a message like the following. (The number you see within the parentheses may vary, depending on how many times you have executed this step before. If doing this step for the first time, there will be no parentheses.) Press the “Keep” button.
2.7 Download the script returned by the EF_Rsync_Script_Generator algorithm
At this point, the script will be downloaded to your computer’s hard disk, and you will see the message at the bottom left of your browser window be replaced by just the name of the downloaded file:
2. 8 Run the script returned by the EF_Rsync_Script_Generator algorithm
Windows users please note: Before proceeding, Windows users will need to complete additional steps to prepare their machine to work with rsync. Please follow the directions here.
After you download the script, from the command line navigate to the directory where the script file is located. This directory will typically be called Downloads, though the location may be different depending on your machine and if you have moved the file. Here is an example:
Once you are in the directory where the file is located, you may be interested in checking the file size to verify that the script exists:
Then run the file you downloaded. It is a shell script. When you run it, a basic features data file and an advanced features data file for each volume in your workset will be transferred to your hard disk via the rsync utility.
If your workset contained N volumes with HathiTrust volume IDs V1, V2, V3,... VN respectively, then executing the shell script as shown above will cause the following compressed advanced and basic feature data files for the corresponding volumes to be transferred to your computer’s hard disk via rsync:
For the workset in this example, because it contained only one volume, the book Buch der Lieder by Heinrich Heine with the HathiTrust volumeID mdp.39015012864743, the script will transfer two files to your machine. They are the advanced and basic feature data files for the volume in the workset:
2.9 Uncompress the downloaded files
Because the advanced and basic feature data files will be downloaded in a compressed format, you will need to uncompress them into JSON-formatted text files.
You will now be able to view the files in the text editor of your choice, and perform text analysis with them using your own code, in the programming language(s) of your choice.