IP Library Granted Patent US 12,242,467
Granted Patent B2
US 12,242,467 · App. 18/492,255 · Granted Mar 4, 2025

Systems and methods for distributed ledger-based data exchange

Inventors: Sean Christopher O'Brien (Atlanta, GA); Maik Andre Lindner (Roswell, GA); Alexis Jorge Liatis (Decatur, GA); Alan Michael Pohl (Doraville, GA)
Assignee: OMNY, Inc.
G06F16/2379G06F21/6245H04L9/3236
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,242,467
App. No.
18/492,255
Granted
Mar 4, 2025
Kind
B2
Abstract

A computer-readable storage medium may include executable instructions stored thereon that, when executed by a processor, may be configured to establish a connection to a node of a distributed ledger network that maintains a distributed ledger. The processor may obtain a first dataset from a first user, perform pre-processing on the first dataset to obtain a first data asset based on the first dataset, and store the first data asset. The processor may calculate a first value for the first data asset and generate a first data proposition based on the first data asset. The processor may obtain acceptance data from a second user, which may include data indicating acceptance by the second user of the first data proposition. The processor may transmit a first distributed ledger record to the node of the distributed ledger network.

Claims (80)

1. A non-transitory computer-readable storage medium having executable instructions stored thereon, wherein the executable instructions, when executed by a processor, are configured to:

establish a connection, over a data network, to a node of a distributed ledger network that maintains a distributed ledger, wherein the distributed ledger includes a cryptographically secure plurality of distributed leger records;

obtain, over the data network, a first dataset from a first user;

perform pre-processing on the first dataset to generate a first data asset based on the first dataset;

store the first data asset;

calculate a first value for the first data asset;

generate a first data proposition based on the first data asset, wherein the first data proposition includes

the first value for the first data asset, and

a description of the first data asset;

obtain, over the data network, acceptance data from a second user, wherein the acceptance data includes data indicating acceptance by the second user of the first data proposition; and

transmit, over the data network, a first distributed ledger record to the node of the distributed ledger network, wherein the first distributed ledger record includes data based on the acceptance data.

2. The computer-readable storage medium of claim 1 , wherein performing the preprocessing on the first dataset includes modifying the dataset, wherein modifying the dataset comprises at least one of:

removing personally identifying data from the first dataset;

shifting a time in the first dataset by a random amount; or

aggregating a plurality of data records in the first dataset.

3. The computer-readable storage medium of claim 1 , wherein the executable instructions, when executed by a processor, are further configured to:

obtain a first hash based on the first data asset;

generate a second distributed ledger record that includes the first hash; and

send the second distributed ledger record over the data network to the node of the distributed ledger network.

4. The computer-readable storage medium of claim 3 , wherein the executable instructions, when executed by a processor, are further configured to:

make the first data asset available to the second user;

obtain a second hash based on the first data asset available to the second user;

obtain the first hash from the distributed ledger network; and

verify that the first hash matches the second hash.

5. The computer-readable storage medium of claim 1 , wherein:

obtaining the first dataset includes decrypting the dataset using a first cryptographic key; and

storing the first dataset includes encrypting the dataset using a second cryptographic key.

6. The computer-readable storage medium of claim 1 , wherein the executable instructions, when executed by a processor, are further configured to:

in response to obtaining the acceptance data from the second user, send a notification to a third user; and

in response to obtaining approval data from the third user, transmit the first distributed ledger record to the node of the distributed ledger network.

7. The computer-readable storage medium of claim 1 , wherein the executable instructions, when executed by a processor, are further configured to permit a third user to view the plurality of distributed ledger records of the distributed ledger network, wherein the third user includes a governmental regulatory body.

8. The computer-readable storage medium of claim 1 , wherein calculating the first value for the first data asset comprises determining an initial value as the first value.

9. The computer-readable storage medium of claim 8 , wherein the executable instructions, when executed by a processor, are further configured to, in response to a predetermined amount of time elapsing since calculating the first value, calculating a second value for the first data asset by adjusting the initial value based on a number of users with a subscription to the first data asset.

10. The computer-readable storage medium of claim 1 , wherein the executable instructions, when executed by a processor, are further configured to:

construct a training dataset based on a plurality of data assets, wherein

the plurality of data assets includes the first data asset,

the training dataset includes a plurality of training records, and

a training record of the plurality of training records includes a current value for a corresponding data asset; and

train a data analytics model on the training dataset.

11. The computer-readable storage medium of claim 10 , wherein calculating the first value for the first data asset comprises performing an inferencing calculation, using the data analytics model, to obtain the first value for the first data asset.

12. A system, comprising:

a distributed ledger network node configured to maintain a distributed ledger, wherein the distributed ledger includes a cryptographically secure plurality of distributed ledger records; and

a server including a computer-readable storage medium having executable instructions stored thereon, and a processor, wherein in response to being executed by the processor, the executable instructions are configured to

establish a connection, over a data network, to the distributed ledger network node,

obtain, over the data network, a first dataset from a first user,

perform pre-processing on the first dataset to generate a first data asset based on the first dataset,

store the first data asset,

calculate a first value for the first data asset,

generate, on a data exchange platform hosted on the server, a first data proposition based on the first data asset, wherein the first data proposition includes

the first value for the first data asset, and

a description of the first data asset,

obtain, over the data network, acceptance data from a second user, wherein the acceptance data includes data indicating acceptance by the second user of the first data proposition, and

transmit, over the data network, a first distributed ledger record to the node of the distributed ledger network, wherein the first distributed ledger record includes data based on the acceptance data.

13. The system of claim 12 , wherein the first dataset comprises at least one of:

pharmaceutical data;

prescription data; or

purchasing data.

14. The system of claim 12 , wherein the first dataset comprises at least one of:

an electronic health record (EHR);

inventory management data; or

data from a smart cabinet.

15. The system of claim 12 , wherein the distributed ledger network comprises a permissioned distributed ledger network.

16. A computer-implemented method for distributed ledger-based data exchange, the method comprising:

establishing a connection, over a data network, to a node of a distributed ledger network that maintains a distributed ledger, wherein the distributed ledger includes a cryptographically secure plurality of distributed ledger records;

obtaining, over the data network, a first data asset from a first user;

storing the first data asset;

calculating a first value for the first data asset by performing an inference calculation using a machine learning model;

generating a first data proposition based on the first data asset, wherein the first data proposition includes

the first value for the first data asset, and

a description of the first data asset;

obtaining, over the data network, acceptance data from a second user, wherein the acceptance data includes data indicating acceptance by the second user of the first data proposition; and

transmitting, over the data network, a first distributed ledger record to the node of the distributed ledger network, wherein the first distributed ledger record includes data based on the acceptance data.

17. The method of claim 16 , wherein calculating the first value for the first data asset comprises determining an initial value as the first value.

18. The method of claim 17 , further comprising, in response to a predetermined amount of time elapsing since calculating the first value, calculating a second value for the first data asset by adjusting the initial value based on a number of users with a subscription to the first data asset.

19. The method of claim 16 , further comprising:

in response to obtaining the first data asset from the first user, generating a second distributed ledger record, including

an identifier for the first user, and

a data asset hash, wherein the data asset hash includes a hash based on the first data asset; and

transmitting, over the data network, the second distributed ledger record to the node of the distributed ledger network.

20. The method of claim 16 , wherein the first distributed ledger record includes an identifier for the second user.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 21, 2024
From: LINDNER, MAIK ANDRE; O'BRIEN, SEAN CHRISTOPHER; POHL, ALAN MICHAEL; LIATIS, ALEXIS JORGE
To: OMNY, INC.
Reel/Frame 067795/0267 →
Continuity (3)
Continuation 17302806 · May 12, 2021
Provisional Application 62704541 · May 14, 2020
Related Publication 20240078226A1 · Mar 7, 2024
References Cited (27)
US 10878124B1 · Sitaraman · 2020 [cited by examiner]
US 11797524B2 · O'Brien et al. · 2023 [cited by applicant]
US 20190332807A1 · LaFever · 2019 [cited by examiner]
US 20200327978A1 · Fower · 2020 [cited by examiner]
US 20210083872A1 · Desmarais · 2021 [cited by examiner]
US 20210357388A1 · O'Brien et al. · 2021 [cited by applicant]
“5 Important Regulations in United States Healthcare,” Maryville University, Web page <https://online.maryville.edu/blog/5-important-regulations-in-united-states-healthcare/>, Aug. 6, 2020, retrieved from Internet Archi… [cited by applicant]
Birkett, Alex, “A Subscription Pricing Strategy that Works,” Web page <https://cxl.com/blog/constucting-pricing-strategy-for-subscription-products/>, May 3, 2020, updated Aug. 3, 2020, retrieved on Aug. 16, 2021. [cited by applicant]
Bozenhardt, Erich H., et al., “Are You Asking Too Much From Your Filler?” Pharmaceutical Online, Web page <https://www.pharmaceuticalonline.com/doc/are-you-asking-too-much-from-your-filler-0001>, Oct. 18, 2018, 2018, re… [cited by applicant]
“BTPO (Brand Price Trade Off),” B2B International, Web page <https://www.b2binternational.com/research/methods/pricing-research/bpto/>, Sep. 28, 2020, retrieved from Internet Archive Wayback Machine <https://web/archive… [cited by applicant]
“Data is a business asset beyond imagination—here is why (and where),” i-Scoop, Web page <https://www.i-scoope.eu/big-data-action-value-context/data-business-asset/>, Jun. 17, 2019, retrieved from Internet Archive Wayba… [cited by applicant]
“Difference Blockchain and DLT,” Marco Polo Network, Web page <https://www.marcopolonetwork.com/articles/distributed-ledger-technology/?redirect=true> Jan. 30, 2018, retrieved on Aug. 16, 2021. [cited by applicant]
“Discrete Choice Model and Analysis,” Columbia Public Health, Web page <http://www.publichealth.columbia.edu/research/population-health-methods/discrete-choice-analysis>, Aug. 16, 2021, retrieved on Aug. 16, 2021. [cited by applicant]
“Distributed Ledger,” Wikipedia, Web page <https://en.wikipedia.org/wiki/Distributed_ledger>, May 7, 2020, retrieved from Internet Archive Wayback Machine <https://web.archive.org/web/20200507030050/https://en.wikipedia… [cited by applicant]
“Equilibrium”, Economics Online, Web page <https://www.economicsonline.co.uk/Competitive_markets/Market_equilibrium.html>, Apr. 21, 2020, retrieved from Internet Archive Wayback Machine <https://web.archive.org/web/2020… [cited by applicant]
“Gabor Granger Pricing Technique,” Web page <https://www.djsresearch.co.uk/glossary/item/Gabor-Granger-Pricing-Technique>, Apr. 3, 2018, retrieved from Internet Archive Wayback Machine <https://web.archive.org/web/20180… [cited by applicant]
“How does government regulation impact the drugs sector?” Investopedia, Web page <https://www.investopedia.com/ask/answers/032315/how-does-government-regulation-impact-drugs-sector.asp>, Dec. 17, 2019, retrieved from In… [cited by applicant]
Kenton, Will, “Regulated Market,” Investopedia, Web page, <https://www/investopedia.com/terms/r/regulated-market.asp>, Nov. 8, 2019, retrieved from Internet Archive Wayback Machine <https://web.archive.org/web/201911081… [cited by applicant]
Kenton, Will, “Walras's Law,” Investopedia, Web page <https://www.investopedia.com/terms/w/walras-law.asp>, Apr. 19, 2019, retrieved from Internet Archive Wayback Machine <https://web.archive.org/web/20190421175422/http… [cited by applicant]
Laney, Doug, “Infonomics: The Economics of Information and Principles of Information Asset Management,” The Fifth MIT Information Quality Industry Symposium, Web page <https://mitiq.mit.edu/QIS/Documents/CDOIQS_201177/P… [cited by applicant]
“Market Mechanics”, MBA Skool, Web page <https://www.mbaskool.com.com/business-concepts/marketing-and-strategy-terms/11345-market-mechanics.html>, May 9, 2017, retrieved from Internet Archive Wayback Machine <https://we… [cited by applicant]
McGuire, John L., et al., Ullmann's Encyclopedia of Industrial Chemistry. doi:10.1002/14356007.a19_273.pub2. ISBN 978-3527306732. [cited by applicant]
“Nash Equilibrium”, Wikipedia, Web page <https://en.wikipedia.org/wiki/Nash_equilibrium>, May 3, 2020, retrieved from Internet Archive Wayback Machine <https://web.archive.org/web/20200503020753/https://en.wilipedia.org… [cited by applicant]
Pettey, Christy, “Treating Information as an Asset,” Garter, Web page <https:www.garter.com/smarterwithgartner/treating-information-as-an-asset/>, Nov. 30, 2017, retrieved on Aug. 16, 2021. [cited by applicant]
“Pharmaceutical Industry,” Wikipedia, Web page <https://en.wikipedia.org/wiki/Pharmaceutical_industry>, May 3, 2020, retrieved from Internet Archive Wayback Machine <https:///web.archive.org/web/20200503135340/https://e… [cited by applicant]
“The Anti-Kickback Statute Basics: Enforcement and Safe Harbors,” Summit Health Law Partners, Web page <https://summithealthlawpartners.com/services/the-anti-kickback-statute> on Aug. 16, 2021, retrieved from Internet a… [cited by applicant]
“What is a conjoint analysis? Conjoint types & when to use them,” Qualtrics XM, Web page <https://www.qualtrics.com/experience-management/research/types-of-conjoint/>, Jan. 17, 2019, retrieved from internet Archive Wayb… [cited by applicant]