This guide explains how to process and combine two CSV files (nsf_collaboration.csv and nsfclimateworkshop.csv) using the Conjoin Networks workflow in SuAVE. Conjoin workflow

Example Input CSVs

Collaboration CSV (nsf_collaboration.csv) 

Name,OAID,Affiliation,Country,City,Number of Collaborators in Scope,Collaborators in Scope
Aditya Akella,https://openalex.org/A5035329776,The University of Texas at Austin,United States,Austin,4,"A5085746671|A5082710354"
Alfred Anderson,https://openalex.org/A5040069168,The Ohio State University at Lima,United States,Lima,0,

Climate Workshop CSV (nsfclimateworkshop.csv) 

Name,OAID,Affiliation,Country,City,OA Concepts
Aditya Akella,https://openalex.org/A5035329776,The University of Texas at Austin,United States,Austin,"Distributed computing|Network routing|Machine learning"
Alfred Anderson,https://openalex.org/A5011242504,University of Chicago,United States,Chicago,"Geology|Volcanology|Chemistry"

Step 1. Import CSVs

  • Import both nsf_collaboration.csv and nsfclimateworkshop.csv.

Step 2. Add Facets

Create extra combined fields to simplify later analysis.

  • Collab Info: Name + Number of Collaborators in Scope
    • Example: Aditya Akella 4
  • Author Info: Name + Affiliation + Country
    • Example: Aditya Akella The University of Texas at Austin United States

Step 3. Merge CSVs

  • Merge key: OAID (the unique author ID)
  • Handle duplicates: Overwrite (workshop data replaces collaboration where overlapping)

Result (merged CSV):

Name,OAID,Affiliation,Country,City,Number of Collaborators in Scope,Collaborators in Scope,OA Concepts
Aditya Akella,https://openalex.org/A5035329776,The University of Texas at Austin,United States,Austin,4,"A5085746671|A5082710354","Distributed computing|Network routing|Machine learning"
Alfred Anderson,https://openalex.org/A5040069168,The Ohio State University at Lima,United States,Lima,0,,
Alfred Anderson,https://openalex.org/A5011242504,University of Chicago,United States,Chicago,,,"Geology|Volcanology|Chemistry"

Step 4. Edit Facets

Remove extra or hidden fields you don’t need:

  • Latitude, Longitude
  • #img, #netvis
  • Show Publications in Scope

Keep only the clean fields you want in the final dataset.

Step 5. Conjoin Networks

  • Input the merged CSV plus the two JSON networks:
    1. Author ↔ Collaborators (from collaboration data)
    2. Author ↔ Concepts (from workshop data)

The Conjoin Networks block unifies them:

  • Nodes = Authors
  • Links = Collaborators + Concepts
  • Attributes = Affiliation, Country, Publications, etc.

ASCII-style example network:

Aditya Akella
   ├── Collaborates with → A5085746671
   ├── Collaborates with → A5082710354
   ├── Works on → Distributed computing
   ├── Works on → Network routing
   └── Works on → Machine learning

Step 6. Export ZIP File

  • Export the result as nsf_conjoined.zip.
  • Upload this ZIP into SuAVE Survey to view the integrated network.

✅ Final Output

When uploaded into SuAVE, the result is an interactive network visualization where:

  • Authors are connected to collaborators and concepts.
  • Each node can be explored by clicking to see its attributes.

Final SuAVE Output