In order to make user held data models useful and efficient, we need to ensure data models follow commonly accepted principles, widely used customs as well as universality to be meaningful and widely compatible.
This project tracks the building of a user held data model and API. It is based on benchmarks such as IAB Techlabs open standard content taxonomy and CINTs open standard taxonomy.
The user data model is used to build customized user data profiles that are accessed using GraphQL. The user makes these profiles available in exchange for customized services by giving permissioned API access, in the form of data profiles.
Access to data profiles is always controlled by the individual by setting permissions by which access to the data profile is granted. The individual has the ability and right to manage those permissions, granting, modifying and revoking them.
To join the discussion on this project and the other repositories, please join the public Liberty Equality Data Slack channel.
This is the initial version of the API.
The current API does not enforce or include the access permissions.
It includes some sample data to understand the data model and possible profile use cases.
This project demonstrates how a data profile could be accessed using the GraphQL API and user data model. Example data profile queries and responses are shown in the README.md of their appropriate sub-directory:
- A media profile where the information made available would be useful for a media company to use to give customized recommendations to the user.
- A local activity profile where the information made available would be useful for a discounting company like groupon to use to give local activity recommendations to the user.
- A basic marketing profile that a user could activate using permissions to allow advertisers to customize ads shown to him if/when we wanted.
A current version of the data model and API is available for download and use.
A hosted version is planned
There are several use cases that are being trialed in segments such as consumer finance, media, travel, similar to this project. Creating different use cases based on this idea is encouraged. For more information and support, please get in touch at [email protected]
This project is licensed under the Mozilla Public License with terms found herein https://en.wikipedia.org/wiki/Mozilla_Public_License
Use of this project requires Python 3 with the following dependencies installed:
pip install SQLAlchemy
pip install graphene_sqlalchemy
pip install Flask
pip install Flask-GraphQL
- models.py - python file containing database models of the user model
- schema.py - python file which defines GraphQL graph structure for database models
- app.py - python file for running GraphQL and GraphiQL views in Flask
- database.sqlite3 - database containing dummy data for demonstration purposes
- fill_db.py - python script for putting data into database (can modify to change dummy data)
- Download the files into a folder on your local computer
- Open the command line and run:
python app.py
- Open http://127.0.0.1:5000/graphql in your browser
- Use the GraphiQL interface to query the database
{
allBasics {
edges {
node {
id
age
name
gender
households {
edges {
node {
id
income
numberofchildren
numberofpersonsinhome
maritalstatus
accomodationtype
}
}
}
occupations {
edges {
node {
id
organization
employeedepartment
employeeprimaryrole
}
}
}
foodandbeverages {
edges {
node {
id
fastfoodweeklyfrequency
alcoholweeklyfrequency
restaurantweeklyfrequency
}
}
}
hobbiesandinterests {
edges {
node {
id
exerciseweeklyfrequency
cinemaweeklyfrequency
favoritemusicgenre
}
}
}
educations {
edges {
node {
id
highestdegree
areaofstudy
}
}
}
}
}
}
}
{
"data": {
"allBasics": {
"edges": [
{
"node": {
"id": "QmFzaWM6MQ==",
"age": 34,
"name": "Melanie",
"gender": "female",
"households": {
"edges": [
{
"node": {
"id": "SG91c2Vob2xkOjE=",
"income": "over 120,000",
"numberofchildren": 1,
"numberofpersonsinhome": 3,
"maritalstatus": "Married",
"accomodationtype": "Apartment"
}
}
]
},
"occupations": {
"edges": [
{
"node": {
"id": "T2NjdXBhdGlvbjox",
"organization": "ExxonMobil",
"employeedepartment": "Petrophysics",
"employeeprimaryrole": "Data Analyst"
}
}
]
},
"foodandbeverages": {
"edges": [
{
"node": {
"id": "Rm9vZGFuZGJldmVyYWdlOjE=",
"fastfoodweeklyfrequency": 0,
"alcoholweeklyfrequency": 3,
"restaurantweeklyfrequency": 3
}
}
]
},
"hobbiesandinterests": {
"edges": [
{
"node": {
"id": "SG9iYmllc2FuZGludGVyZXN0czox",
"exerciseweeklyfrequency": 5,
"cinemaweeklyfrequency": 1,
"favoritemusicgenre": "rock"
}
}
]
},
"educations": {
"edges": [
{
"node": {
"id": "RWR1Y2F0aW9uOjE=",
"highestdegree": "Masters",
"areaofstudy": "Petroleum Engineering"
}
}
]
}
}
},
{
"node": {
"id": "QmFzaWM6Mg==",
"age": 55,
"name": "Steve",
"gender": "male",
"households": {
"edges": [
{
"node": {
"id": "SG91c2Vob2xkOjI=",
"income": "50,000 to 60,000",
"numberofchildren": 2,
"numberofpersonsinhome": 4,
"maritalstatus": "Married",
"accomodationtype": "House"
}
}
]
},
"occupations": {
"edges": [
{
"node": {
"id": "T2NjdXBhdGlvbjoy",
"organization": "Google",
"employeedepartment": "Marketing and Sales",
"employeeprimaryrole": "Sales Engineer"
}
}
]
},
"foodandbeverages": {
"edges": [
{
"node": {
"id": "Rm9vZGFuZGJldmVyYWdlOjI=",
"fastfoodweeklyfrequency": 2,
"alcoholweeklyfrequency": 0,
"restaurantweeklyfrequency": 2
}
}
]
},
"hobbiesandinterests": {
"edges": [
{
"node": {
"id": "SG9iYmllc2FuZGludGVyZXN0czoy",
"exerciseweeklyfrequency": 1,
"cinemaweeklyfrequency": 2,
"favoritemusicgenre": "classic"
}
}
]
},
"educations": {
"edges": [
{
"node": {
"id": "RWR1Y2F0aW9uOjI=",
"highestdegree": "Masters",
"areaofstudy": "Business Administration"
}
}
]
}
}
}
]
}
}
}