diff --git a/CITATION.cff b/CITATION.cff
index 4c6fd26..589a436 100644
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -5,7 +5,7 @@ cff-version: 1.2.0
 title: >-
   Creating reproducible packages when data are confidential
 message: >-
-  Presented at the 2022 FSRDC Conference. The opinions 
+  Presented at the 2024 FSRDC Conference. The opinions 
   expressed in this talk are solely the authors, and do not 
   represent the views of the U.S. Census Bureau, the American 
   Economic Association, or any of the funding agencies.
@@ -17,15 +17,10 @@ authors:
     affiliation: Cornell University
     orcid: 'https://orcid.org/0000-0001-5733-8932'
 repository-code: >-
-  https://github.com/larsvilhuber/reproducibility-confidential-fsrdc/
+  https://github.com/labordynamicsinstitute/reproducibility-confidential/
 abstract: >-
-  The American Economic Association's Data Editor has
-  reviewed more than 1,000 empirical articles since
-  July 2019, and worked with authors to improve the
-  reproducibility of their research compendia
-  (replication packages). Some lessons emerge from
-  this work. In this presentation, I will focus on
-  lessons for scholars using confidential data, in 
-  particular in the FSRDC.
-license: CC-BY-4.0
-date-released: '2022-09-23'
+  In this presentation, I focus on
+  techniques to improve reproducibility for scholars using confidential data, in 
+  particular in the US FSRDC.
+license: CC-BY-NC-4.0
+date-released: '2024-09-13'