Research data · De-identification

From raw export to share-ready dataset, with the record to prove it.

naoveil checks every column of a clinical CSV or Excel file with you, and keeps patient aliases and date gaps consistent from one export to the next.

From: naosuu LLC
Status: Development alpha · pilot in preparation
Runs in: Excel add-in · desktop app · command line
Correspondence: [email protected]

In short

For: Research teams that share patient-level spreadsheets: data managers, investigators and the reviewers who approve each data request.
What it does: Removes or disguises names, IDs, birth dates and other identifying details in a CSV or Excel file, column by column, with a person approving every change.
Why it helps: Collaborators get data they can still analyze, and reviewers get a record of exactly what was changed and why.

Ask about the pilot See how teams use it ↓

1Who it's for

naoveil is a tool for removing identifying details from research spreadsheets before you share them. It is built for the three people involved in every data request.

Prepares the data

Clinical research data managers

You turn study exports into files that can leave the team. naoveil replaces hand-built macros and manual edits, works inside Excel, and gives you the same careful process every time.

Shares the data

Investigators and study teams

You need to send data to collaborators, consortium partners or a journal. naoveil gets it ready without weeks of back-and-forth and without losing the patient timelines your analysis depends on.

Approves the data

Privacy and compliance reviewers

You sign off on data requests. Every naoveil export comes with a record of what was removed, what was kept and why, so you can review it without chasing anyone.

2Use cases

Sending a dataset to an outside collaborator

A partner site asks for your cohort data. Names and record numbers come out, dates are shifted, and the file is ready to send, with a record your privacy office can check.

Monthly exports from a long-running study

Each export uses the same study mapping, so a patient who is Subject_0137 in January is still Subject_0137 in June, and the files join cleanly (Fig. 2).

Data for a publication or repository

Journals and funders often ask for shareable data. Prepare a de-identified copy for your data availability statement and keep the record of how it was made.

Answering a data-use or ethics review

When a reviewer asks how the data was prepared, hand them the processing record instead of reconstructing the steps from memory.

Fig. 1 · Interactive

parkinson_cohort_export.csv · 6 of 100,000 rows · synthetic

Patient_IDraw	Full_Nameraw	Date_of_Birthraw	Ageraw	Diagnosis_Dateraw	Enrollment_Dateraw	H&Y_Stageraw	Gapdays
P-10442	Alfred Pennyworth	1933-04-11	88	2021-06-02	2021-07-19	2.5	47
P-10587	Bruce Wayne	1954-11-02	67	2022-01-11	2022-02-28	1	48
P-11023	Selina Kyle	1946-08-19	74	2020-11-30	2021-01-04	3	35
P-11290	Harvey Dent	1964-09-30	58	2023-03-17	2023-05-02	1.5	46
P-11871	Pamela Isley	1937-05-22	82	2019-09-05	2019-10-21	2	46
P-12004	Oswald Cobblepot	1959-12-07	63	2022-12-12	2023-01-30	2.5	49

Patient_IDpseudonymize	Full_Nameredact	Date_of_Birthgeneralize	Agegeneralize	Diagnosis_Datedate shift	Enrollment_Datedate shift	H&Y_Stagepreserve	Gapdays
Subject_0137	[REDACTED]	1933	80-89	2021-02-22	2021-04-10	2.5	47
Subject_0212	[REDACTED]	1954	60-69	2022-08-11	2022-09-28	1	48
Subject_0049	[REDACTED]	1946	70-79	2020-10-24	2020-11-28	3	35
Subject_0318	[REDACTED]	1964	50-59	2024-01-12	2024-02-27	1.5	46
Subject_0077	[REDACTED]	1937	80-89	2019-01-04	2019-02-19	2	46
Subject_0256	[REDACTED]	1959	60-69	2023-02-08	2023-03-29	2.5	49

Fig. 1. Lift the veil. Drag across the table to compare the raw file on the right with what naoveil produces on the left. Names are removed, patient IDs become study codes, birth dates keep only the year and ages become ranges. Dates move, but the time between diagnosis and enrollment stays the same, so the data is still useful for analysis. changedkept, with a reason

3How it works

Open your file
A CSV or Excel file, or the worksheet you already have open in Excel.
Review the suggestions
naoveil flags names, IDs, dates, places and health details, and suggests what to do with each column. You decide. Nothing can be exported until every column has a decision.
Process it on your computer
Names are removed, IDs become study codes, birth dates keep only the year, and each patient's dates shift together so timelines stay intact.
Share it with the record
Export the cleaned file and a record of every decision, ready for your collaborator and your reviewer.

Fig. 2 · Interactive · runs in your browser

Study mapping: none yet

Month 1 export

Patient_ID	Full_Name	Visit_Date	Aliasfrom Patient_ID	Full_Name	Shifted visit

Month 2 export

Patient_ID	Full_Name	Visit_Date	Aliasfrom Patient_ID	Full_Name	Shifted visit	Gap since month 1

Process month 1 to create a study mapping. Then process month 2 with it, or with a new one, and compare.

Fig. 2. Same patient, same code, every month. Each table shows the raw export on the left and what naoveil produces on the right. Process month 1, then process month 2 with the study mapping from month 1: returning patients keep their code and the real time between their visits. Try a new mapping instead and they can no longer be linked. This demo runs naoveil's own rules in your browser; nothing is sent anywhere.

4What your reviewers receive

Every export comes with a processing record. It answers the question reviewers always ask: how was this data prepared?

Column	What naoveil did	Note
Full_Name	Removed	Direct identifier
Patient_ID	Replaced with study codes	Same codes as last month's export
Date_of_Birth	Reduced to the year	Changed by reviewer from "remove"
Diagnosis_Date	Shifted, timeline kept	Same shift for each patient's dates
H&Y_Stage	Kept	Reason: "primary endpoint (protocol §4.2)"

The record also identifies the exact source file and the naoveil version used, so the export can be traced later.

5Where it runs

Excel add-in

Works on the sheet you have open, in Excel for Mac, Windows and the web. It adds the cleaned data and the record as new sheets and never changes your original.

Desktop app

For CSV and Excel files on Windows and Mac. It saves only where you choose and warns you before saving to a cloud-synced folder.

Command line

For teams that automate their exports and want the same steps run the same way every time.

6What naoveil doesn't do

It doesn't certify your data. naoveil helps you prepare the data and records each decision. Your IRB or privacy office still decides whether it can be shared.
It suggests; you decide. Its suggestions can be wrong, which is why every column needs a person's review.
Coded data can still be personal data. Handle the cleaned file as your data agreement requires.
It works on columns, not free text. It won't find a name written inside a clinical note.
Keep the study mapping safe. Without the file and its passphrase, future exports can't reuse the same codes.
Excel for the web stores your workbook online. naoveil processes it in the add-in, but the workbook lives in your Microsoft account.

7Questions and answers

What is naoveil?

naoveil is a tool for removing identifying details from research spreadsheets before they are shared. It is made by naosuu LLC. It checks each column of a CSV or Excel file, suggests what to remove or disguise, lets a person approve every change, and exports a cleaned copy with a record of what was done.

Who is naoveil for?

naoveil is for research teams that share patient-level data: clinical research data managers who prepare exports, investigators who share data with collaborators, and privacy or compliance reviewers who approve data requests.

Does naoveil upload my data?

No. naoveil works on your computer, in Excel or in the desktop app, and does not send your data to naosuu or any other service. If you use Excel for the web, your workbook is stored in your Microsoft account as usual.

Does naoveil make a dataset anonymous or HIPAA compliant?

No. naoveil does not certify that a dataset is anonymous or HIPAA compliant. It helps you prepare the data and records every decision, and your IRB, privacy office or a qualified expert makes the final call.

Can the same patient keep the same code across monthly exports?

Yes. naoveil remembers the codes in an encrypted study mapping file protected by your passphrase. Load that file for the next export and returning patients keep the same code and the same date shift, while new patients get the next free code. Patient IDs must match exactly, and if you lose the file or the passphrase, later exports cannot reuse the codes.

How does naoveil change dates without ruining the analysis?

Each patient's dates move forward or back by the same number of days, up to a year, so the time between that patient's visits, diagnosis and treatment stays exactly the same.

Is naoveil available now, and how much does it cost?

naoveil is in development, and a small research pilot is being prepared. Pricing has not been announced. To ask about the pilot, email [email protected].

8Join the pilot

We're preparing a small pilot with research teams that share patient-level data with collaborators at least once a month.

naoveil is in development and has been tested in Excel for Mac, Windows and the web, and on files of 100,000 rows. Tell us your role, where your data comes from (REDCap, an EHR extract, a registry), typical file sizes, and whether you work on Windows or Mac. Please don't send any data.

Ask about the pilot Request Excel setup guidance

Or write to [email protected]