NSF award 2551201 · Columbia University

HCC: III: Database Visualization Theory and Practice

Final report due

28 January 2031

in 1,563 days · The award ends on 30 September 2030.

GrantClerk is a private service. We are not NSF or any government agency.

Dates this award owes

NSF emails you about this too.

Decide about an extension2 Jun 2030in 1323 days
award ending 2030-09-30 · Research.gov
This one is ours, not NSF’s.
Extension request16 Aug 2030in 1398 days
award ending 2030-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2030in 1433 days
award ending 2030-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2031in 1563 days
award ending 2030-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2031in 1563 days
award ending 2030-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2031in 1563 days
award ending 2030-09-30 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

Annual report dates come from the budget period on your award notice. That date is not public, so it is not shown here.

How we got this date

NSF lists this award's end date as 30 September 2030.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2031.

Read the rule on Research.gov

Get a note before each report date

Add this award to your desk. We email you before each date and keep the dates in one place.

Renews each year until you cancel. Cancel any time from your account.

Already a member? Sign in

Award card

Award number: 2551201
Period of support: 1 Oct 2026 – 30 Sep 2030
Amount: $500,000
Awardee: Columbia University, NEW York, NY
Program: HCC-Human-Centered Computing
Directorate: CSE

Abstract

Data visualization tools like Tableau and Excel have transformed how scientists, businesses, and the public make sense of information. But these tools share a hidden limitation: they can only work with data that has been manually flattened into a single spreadsheet-like table. In reality, most data is stored in relational databases — collections of linked tables that capture rich relationships, such as how patients…

Is this right?

We copy this from the public NSF award record. Your award notice and NSF always win. If a date looks wrong, check Research.gov.