Liabilities / Assets
69th percentile
Tied with the lowest-debt nonprofits in its peer group.
Data Nutrition Project Inc.
990EZ • Fiscal year 2023 • EIN 84-2225081
Siviq Scores
Precomputed percentiles for this filing year versus similar nonprofits in the same peer cohort.
0.00x
Liabilities / Revenue
71st percentile
Tied with the lowest-debt nonprofits in its peer group.
Net Margin
83rd percentile
Higher net margin than 83% of similar nonprofits.
Top Officer Pay
87th percentile
Higher top officer pay than 87% of similar nonprofits.
Top officer pay equals 0.0% of source-year revenue.
Asset Growth
90th percentile
Faster asset growth than 90% of similar nonprofits.
Revenue Growth
86th percentile
Faster revenue growth than 86% of similar nonprofits.
Balance Sheet
Assets
Up$104,005
Up $83,599 (+410%) from 2022
Net Assets
Up$104,005
Up $83,599 (+410%) from 2022
Liabilities
Flat$0
Flat from 2022
Revenue And Expenses
Revenue
Up$134,500
Up $73,350 (+120%) from 2022
Expenses
Down$50,901
Down $29,843 (-37%) from 2022
Net Income
Up$83,599
Up $103,193 (+527%) from 2022
Historical Trend
Jump To
Filing Snapshot
- Filing Period
- Jan 1, 2023 to Dec 31, 2023
- Signed
- Apr 1, 2024
- Return Version
- 2023v5.0
- Gross Receipts
- $134,500
Mission and Program Overview
Mission
The Data Nutrition Project creates dataset quality standards and fosters conversations around the topics of responsible data creation and use. Our belief is that deeper transparency into dataset health can lead to better data decisions, which in turn lead to better Al. Founded in 2018 through the Assembly Program at the Berkman Klein Center at Harvard University, our research team takes inspiration from nutritional labels on food, aiming to build labels that highlight the key ingredients in a dataset. Examples include metadata and populations, unique or anomalous features regarding distributions, missing data, and comparisons to other 'ground truth' datasets.
Program Services
| Description | Grants | Expenses |
|---|---|---|
| The Data Nutrition Project creates dataset quality standards and fosters conversations around the topics of responsible data creation and use. Our belief is that deeper transparency into dataset health can lead to better data decisions, which in turn lead to better Al. Founded in 2018 through the Assembly Program at the Berkman Klein Center at Harvard University, our research team takes inspiration from nutritional labels on food, aiming to build labels that highlight the key ingredients in a dataset. Examples include metadata and populations, unique or anomalous features regarding distributions, missing data, and comparisons to other 'ground truth' datasets. Form 990-EZ, Part V - Regarding Transfers Associated with | $134,500 | $50,901 |
Compensation and Service Providers
Employees
| Name | Title | Full / Part Time | Base | Other | Total |
|---|---|---|---|---|---|
| Mary Gray | President | PT | $0 | - | - |
| Jessica Larkin Fjeld | Secretary | PT | $0 | - | - |
| Joshua Joseph | Treasurer | PT | $0 | - | - |
Filing and Contact Details
Filer
- Filer Name
- Data Nutrition Project Inc
- EIN
- 84-2225081
- Phone
- 6467504953
- Address
- 25 Duncan Avenue Apt 213, Jersey City, NJ 07304
Signing Officer
- Name
- Joshua Joseph
- Title
- Treasurer
- Phone
- 6467504953
- Signed
- 2024-04-01
- Discuss with paid preparer
- Yes
Preparer
- Firm
- Schwartz & Gomez Tax and Accounting LLP
- Address
- 222 Bidwell Avenue, Jersey City, NJ 07305
- Preparer
- Sara Schwartz
- Phone
- 2013328703
Supplemental Narrative
Additional Explanations
Form 990-EZ, Part I, Line 16
“Description;Amount^Bank Fees;23|Food and Travel;1278|Research;6486|Software;2405|Supplies and Materials;3740^Total;13932^”
Raw XML Appendix167 raw XML fields
This appendix keeps the raw XML leaves available for debugging and edge-case review. The human report above is the primary experience.
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| IRS990EZ/PrimaryExemptPurposeTxt | 0 | The Data Nutrition Project creates dataset quality standards and fosters conversations around the topics of responsible data creation and use. Our belief is that deeper transparency into dataset health can lead to better data decisions, which in turn lead to better Al. Founded in 2018 through the Assembly Program at the Berkman Klein Center at Harvard University, our research team takes inspiration from nutritional labels on food, aiming to build labels that highlight the key ingredients in a dataset. Examples include metadata and populations, unique or anomalous features regarding distributions, missing data, and comparisons to other 'ground truth' datasets. |
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Document Assets
No mirrored PDF or thumbnail assets are attached yet.
Filings
Displayed year
2023 • Form 990EZDetailed filing. Detailed filing data is available for this year.
- Assets
- $104,005
- Liabilities
- $0
- Net assets
- $104,005
- Revenue
- $134,500
- Expenses
- $50,901
- Net income
- $83,599