TESTIMONY
Rachael Fauss, Senior Policy Advisor, Reinvent Albany on Enhancing the New York City Open Data Program
1:24:34
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3 min
Rachael Fauss, Senior Policy Advisor for Reinvent Albany, discusses the need for improvements and expansion in New York City's Open Data program.
- Fauss highlights New York City's pioneering role in passing the world's first open data law and its importance for transparent and accountable government.
- She emphasizes the necessity of automating half of the datasets that remain unautomated to ensure the program's success.
- Fauss praises the 2023 oversight hearing for generating public interest and discussing ways to continuously improve the Open Data program.
- She calls for increased resources and staffing to match the efforts of the MTA's open data team, suggesting a need for at least 15 full-time staff.
- Fauss concludes by underscoring the significance of continuous improvement efforts and the creation of technical standards and policy documents to support the program.
Rachael Fauss
1:24:34
Hi.
1:24:34
Good morning.
1:24:35
Cher Gutierrez and council member Paladino.
1:24:39
My name is Rachel Foss, and I'm the senior CAdvisor for reinvent Albany.
1:24:43
Every reinvent Albany advocates for transparent and accountable government in New York State, and we were instrumental in drafting and passing New York City's 20 12 open data law.
1:24:52
I was testified about it more than 10 years ago in a with a different hat, so it's nice to be back today.
1:24:59
When we thank you for holding this oversight hearing.
1:25:01
And thanks to the leadership of the council, New York City passed the world's first open data law in our successes and failures are closely watched by government everywhere.
1:25:11
Before getting into some of the analysis of the 2023 open data report published by OTI, I wanted to highlight two principles we think are really important that'll make open data successful.
1:25:21
This hearing today is very important, and it's important for two reasons.
1:25:25
1 is the public pressure and showing that there is public interest and indeed for this.
1:25:31
And the other I think is that looking at ways to continuously improve the program.
1:25:37
2nd, we really wanna highlight automating open data as a very high priority.
1:25:43
And I'll say it this way.
1:25:45
I think it's important automation to happen because of the limited resources.
1:25:51
We noted in our testimony there are 3 437 datasets that have 435, excuse me, that have not yet been automated.
1:26:01
That's about half of the total list of datasets that are able to be automated.
1:26:06
Appreciated the OTI explaining a little bit about the process there, but I I would love to see a dataset for that specifically in terms of the schedule, you know, how quickly can we get these things automated and highlighting some of the issues around, you know, is this something that's only updated every 10 years?
1:26:26
You know, having that information would be helpful so we can get a better sense of the progress in that area and the challenges.
1:26:32
Right?
1:26:34
We appreciate a lot of the continuous improvement efforts the policy documents, the creation of that dashboard, continuation of open data week with beta NYC.
1:26:45
We've We are big fans of school of data and a lot of the events around open day to week, and it gives some good visibility of the program.
1:26:52
We also appreciate, you know, the the technical standards and policy docs.
1:26:56
And these will help the program succeed.
1:26:58
On the budget front, I second, the notion that get back at least where we used to be, I'd like to give sort of comparison.
1:27:08
We work a lot with the MTA open data team.
1:27:10
And they have 3 full time staff just on open data.
1:27:14
And they have 46 agency staffers within the MTA that are those data stewards.
1:27:19
They're about a 5th the size of New York City.
1:27:22
So, you know, that would say, 15 staff if you were to be at the MTA levels.
1:27:27
At the same time, the MTA staff have told me repeatedly that they don't have enough, you know, three people is way way too small for the amount of work they have to do.
1:27:36
So I think, you know, if you scale it up, it really shows you that you there needs to be a lot more resources.
1:27:46
My testimony goes into a few things that I just encourage you to look at later.
1:27:50
We looked at 3 of the metrics, documents, metrics, datasets, the foil metrics, the automation metrics, and then the what else do I look at?
1:28:00
Data set removal.
1:28:02
We've got some interesting stats on there on where agencies are doing well and where they're not doing well.
1:28:07
And I just encourage you to look at that if you wanna look at individual agency compliance issues.
1:28:12
So thank you so much.
1:28:13
Rachel.
