Note to students

This website is organized as follows. The side navigation serves a static menu to navigate across pages on this website. We provide you with a template of what we want to see from your project pages, the contents can be edited on a per project basis.

Abstract

We plan to develop an ontology-enabled system that allows a comparison between these various outlets and journalists that accounts for a difference in terminology and content focus that results from media outlets appealing to different audiences. Users need to be able to connect various articles across media outlets to the same journalist or editor. The ontology serves the purpose of providing a way to link these articles and events that is robust to biased reporting. Users need a way to connect politicians or prominent figures to pieces of legislation, political issues, other politicians, political parties, elections, and articles.

A critical component of functioning democracies is a voting populace with the information necessary to make an informed vote. The relaying of this information should naturally facilitate rational citizens in voting in a manner that best suits their well-being and beliefs. Due in part to the advent of the digital age and the ad-view revenue model dominating media, there are perverse incentives that favour viewer engagement over unbiased and factual reporting. This perverse media incentive structure naturally results in outlets finding a position on this bias/accuracy continuum that caters to a specific cross section of viewers to maximise engagement and build a viewer base. As a result outlets choose editors, journalists, stories, and language that best appeals to this base and is largely responsible for today’s polarised media climate.

Workflow Diagram

Add a representative diagram of your project such as the below workflow diagram illustrating the flow between the components.

Our knowledge representation approach backed by our study cohort ontology and the knowledge graphs instantiating Table 1 data, are built to support analytical applications to determine applicability of a study population to a patient. Our data sources include cited research studies from the pharmacologic and cardiovascular complications chapters of the ADA Standards of Medical Care guidelines, and patient records selected from the NHANES 2015-2016 questionnaire. Our population analysis scenarios are designed to determine if studies match, if there are limitations and to evaluate their quality. Additionally, we visualize similarity of a group of study subjects (arm) to a patient.

List of Resources

List resources you think a reader would benefit from to use your project. We list some examples you could make available below.

Resources	Links
1. Ontology	(a) Your Ontology
2. Term List	(a) Mapped Vocabularies
2. Competency Questions	(a) SPARQL Queries
3. Presentations:	(a) Project presentations during class

Acknowledgements

Please acknowledge people who have helped you in this work. An example is below

This work is undertaken as a part of the Health Empowerement by Analytics, Learning and Semantics (HEALS) project , and is partially supported by IBM Research AI through the AI Horizons Network. We thank our colleagues from IBM Research, Dan Gruen, Morgan Foreman and Ching-Hua Chen, and from RPI, John Erickson, Alexander New, Neha Keshan and Rebecca Cowan, who provided insight and expertise that greatly assisted the research.