QUESTION
What is the percentage of NYC data updates done on time, and what efforts are being made to improve this?
1:02:29
·
3 min
Approximately 63% of NYC's datasets are updated on schedule, with efforts underway to improve the definition of 'on time' and increase this percentage.
- Council Member Gutiérrez questions the timeliness of data updates for existing datasets and seeks opportunities for improvement.
- NYC Office of Technology and Innovation (OTI) reports about 63% of datasets are updated on time, not considering those updated on irregular bases.
- The definition of 'on time' is under review to better reflect actual dataset update frequencies and enhance data transparency.
- This conversation underscores the importance of data transparency, accountability, and building trust in government through regular and accurate data updates.
Jennifer Gutiérrez
1:02:29
And in the last, I'll say, 2 years, roughly, what is the percentage of data that are updated on time or whatever whatever time frame that you can give to me.
Martha Norrick
1:02:46
Datasets that are currently published that get updated sort of on a on a based on their own timeline.
1:02:52
Right?
1:02:52
Are you talking about datasets that haven't been released yet or datasets that are already released?
Jennifer Gutiérrez
1:02:56
That are already released.
Zachary Feder
1:02:58
So updating existing.
1:03:00
So updating existing datasets, not publishing brand new ones.
Martha Norrick
1:03:03
How frequently do the daily datasets get updated daily?
1:03:12
We're looking at the dash.
1:03:13
Sure.
Jennifer Gutiérrez
1:03:14
I mean, I'm curious to see I mean, I'm looking for opportunities to improve.
1:03:17
Obviously, a big a big benefit to having having this law and this tool is a lot of what my colleagues here said.
1:03:25
It is about transparency.
1:03:26
It's a 100% about accountability, but it's also about, like, promoting trust.
1:03:31
That New Yorkers have in government.
1:03:34
And so if I'm getting complaints where they where where folks feel that certain agencies are behind on providing that data that they themselves have determined are able to provide by a certain timeline That is, like, you know, there has to be accountability.
1:03:50
So that's why I asked that question, but I'm also looking for opportunities to improve.
1:03:54
So if you have a a sense of the percentage of agencies that are on time, that are are doing well, that are doing their thing responsibly.
Zachary Feder
1:04:05
So right now, if you exclude all of the historical datasets or the datasets that are updated on some irregular or less predictable basis.
Martha Norrick
1:04:17
Mhmm.
Zachary Feder
1:04:19
We currently have around 63% of our of of the data sets that we can track to be on time Okay.
1:04:26
Are on time.
Jennifer Gutiérrez
1:04:27
Yeah.
1:04:27
And it's the the reason primarily what Mark that said.
1:04:31
I guess when, like, folk, when you're checking in with these agencies, what is the reason that agencies are saying they're unable provided?
Zachary Feder
1:04:38
So I I think there is, in some cases, it it's really a matter again of, like, how do we how do we define on time Mhmm.
1:04:47
And we're continuing to improve that definition.
1:04:51
So right now, we when a dataset is we have, let's say, an automatic check every day for a dataset.
1:05:01
Mhmm.
1:05:01
And that what we say publicly is, well, this dataset is dated daily because we check for new data each day.
1:05:07
If we check for new data and nothing changed for a day, for a week, that dataset doesn't change.
1:05:13
Mhmm.
1:05:13
And our records would say, well, this dataset's not updated on time.
1:05:17
When in reality, it's it's just reflecting that no data has come in for a day or for a week.
1:05:23
So it it's on time.
1:05:25
It just our automation is working.
1:05:27
It's running.
1:05:28
All the data's there.
1:05:29
So there there's a question of, like, definitions that we're getting at.
1:05:32
And one thing we've started to do with that is differentiate between how often do we check for new data versus how often do we expect new data.
1:05:41
So that number, the 63% will be increasing as that continues to propagate, and we get a better understanding of that distinction.
Jennifer Gutiérrez
1:05:51
Mhmm.
1:05:51
Thank you.
1:05:52
Thank you.
1:05:54
Have a couple more questions, and then I'm gonna pass it off to my colleague, accounts member, Paladino, for questions.
