IDS pulls in relevant scholarly data from a wide range of trusted external sources including Scopus, OpenAlex and Crossref. Below is the high level process:

1. IDS takes your roster details
2. Identifies the faculty member from the name, email, and institution in Faculty Activity Reporting (FAR)
3. Searches for books, book chapters, journal articles, and proceedings found using the following sources: Scopus, Open Alex & Crossref
4. Returns the data and deduplicates against data already in FAR
5. Presents data to faculty/administrator to accept or reject
6. Accepted Data is then added to FAR 

Before records are shown to scholars, IDS will automatically:

• Format data to ensure it will import into FAR correctly
• Match records to the correct scholars (even with similar names) through disambiguation  using data associated to the scholar (ORCiD or Scopus Author IDs) and the records (DOI) it is bringing in.
  

  Integration with individual ORCiD accounts is also possible through the FAR module.

   
• Consolidate duplicate data: IDS automatically deduplicates recommendations by comparing fields like type, date, journal, title and authors with existing FAR records, giving equal weight to all fields. This process does not apply to data managed by the Data Services team or manually entered by faculty. All fields (such as type, date info, journal, location, number, info, pages, publisher, title, volume, year info, and author) have equal weight during the comparison.
  • If the total match % of all fields is:
    • < 82% then it is flagged as a new item and is added to their queue to validate.
    • > 82% then it is assumed to be a duplicate and IDS will not show it as a recommendation.
  • If the matched record and imported record has empty values for one of the fields being compared, then that field is ignored in the calculations.
  • Deduplication does not remove extra white spaces and is case-sensitive, meaning entries with different capitalization will be treated as distinct.
  • The Data Service avoids presenting duplicate data already in the FAR module by using deduplication scripts that check against the FAR database during the IDS data refresh. Faculty should accept IDS recommendations before manually adding scholarly records, as deduplication only occurs if the data found with IDS has been added to FAR first. If data is added to FAR after IDS runs, deduplication will not take place 

To bulk accept activities under the ‘Need Review’ tab, check the boxes next to the activities you want to accept, then click on the Accept Activities button on the toolbar above.

• Where recommendations are complete, these records will automatically be accepted and added to FAR.
• Where recommendations do not have required fields completed, these will be highlighted, and you will need to go through each item separately and include the missing data and accept. 
  

To bulk delete activities, check the boxes and then click the Delete button. Deleted activities will move to the ‘Deleted’ tab and will no longer be shown to the user. 

• If you delete something by mistake, go to the ‘Deleted’ tab, select the activity, and then click the Restore button to move it back to the ‘Need Review’ tab.
  

1. To edit, accept, or delete activities, click the hyperlinked title of the desired activity to open the Step 1: Record Information window on the right-hand side. 
   
2. Fill out Step 1: Record Information and Step 2: Activity Classifications.
   

IDS pre-populates FAR with bibliographic data about faculty scholarship pulled in via integration with CrossRef and OpenAlex for easy validation by faculty members or their proxies. Types of scholarship available via the IDS include books, book chapters, journal articles, and proceeding publications.

Yes, IDS is refreshed regularly with current data for all faculty members in the service.

• Data is updated simultaneously for all clients on a recurring basis.
• After removing duplicates and verifying the data, IDS presents the data to faculty for validation through a workflow similar to the existing Activity Input Workflow in the FAR module.
• Once a faculty member or proxy validates the citation, it will appear in FAR.

Not seeing your latest scholarly activity? If something new has been published since the last update, it may still be on its way to the Homepage. If it is not time sensitive, give it time. If it does not appear in the next update, it may not have been captured in our source data pool. You might need to enter it manually or search an individually linked data source if applicable. For time-sensitive entries, manual entry or a search through linked sources will be necessary.

Currently, IDS can only pull data from sources automatically connected to the Data Service. The Interfolio FAR module still offers all of the existing data input options.

Auto-accept means that records with a confidence score above the set threshold are automatically imported and accepted into the system without manual review.

Currently, there are no direct notifications. However, you should see indicators in the system stating whether records were auto-accepted or manually reviewed.

The confidence score reflects our confidence that we have identified the correct person, based on matching their name, institution, and email.

No, the threshold is set by your institution's administrators and updated by the team supporting its implementation. You can review which records are accepted or rejected but not change system settings.

You can review the records flagged for manual review and choose to accept or reject them. For auto-accepted records, contact your administrator if discrepancies are found.

You should see a message indicating that the record was auto-accepted by your institution, based on confidence scores. The labelling for this is IDS (Automatically imported by institution) and FAR (Interfolio data Service: Automatically imported by institution).

Accepted records will automatically appear in your Web Profile and FAR, reflecting your approved scholarship data.

Your institution's support or administrative team is responsible for communicating and explaining how auto-approval impacts your data.