AI LA Community, Inc
1 active project
Visualizing Health Data as Interconnected Entities
Scientific Questions Being Studied
Hypothesis: Creating and visualizing a graph data structure (a specific type of structure to organize data that contains information about the relationships between data as well as characteristics or attributes of the data), will help participants and researchers understand and discover connections with the data.
- Disease Focused Research (diabetes mellitus)
- Create data structures (ontologies) from All of Us data that contain the properties and relations between the data.
- Visualize this structured data with circles for concepts or entities and lines connecting these entities to represent relationships between them. The lines (relationships) will have labels describing what kind of relation the entities have.
- Tools to create these data structures include:
- Programming languages: Python3
- Python libraries: Pandas, rdflib, matplotlib, seaborn
- Semantic technology: RDF, SPARQL
- Linked Open Data: DBpedia, Ontology for General Medical Science, CIDO: Ontology of Coronavirus Infectious Disease
- That visualizing participant data with this graph structure will help both participants and researchers to gain understanding of the disease as well as help to discover connections between the data that otherwise would be invisible using other forms of data visualization.
Demographic Categories of Interest
- Race / Ethnicity
- Sex at Birth
- Gender Identity
- Sexual Orientation
- Access to Care
- Education Level
- Income Level
Data Set UsedRegistered Tier
- Jon Sundin - Other, AI LA Community, Inc
You can request that the All of Us Resource Access Board (RAB) review a research purpose description if you have concerns that this research project may stigmatize All of Us participants or violate the Data User Code of Conduct in some other way. To request a review, you must fill in a form, which you can access by selecting ‘request a review’ below.