Class Projects

Classes: Ontology Engineering Spring 2016


Rui Yan - knowledge engineer, software engineer
Hao Zhong - knolwedge engineer, software engineer, domain expert (certified soccer referee affiliated with United States Soccer Federation and National Intercollegiate Soccer Officials Association)

Classes: Ontology Engineering Spring 2016

The ANNO Team

Matt Klawonn, MD Ridwan Al Iqbal, Spencer Norris


Welcome! You have found the Artificial Neural Network Ontology, or ANNO. Our goal is to create an ontology to recommend weight initializations for Keras neural network models, with the hope of extending to other artificial neural network libraries.

Classes: Ontology Engineering Spring 2017

What We Are Doing:

Using ontological engineering, Culture Shock seeks to provide comprehensive answers to questions about a particular subset of television shows (i.e. Atlanta) and the political themes covered within them. The questions we seek to provide answers include items such as: Does Lee experience Police Brutality? and Is Alfred Miles trolled by Zan? In an effort to achieve our goal, Culture Shock uses holistic methods to ensure that perspectives from culture, legislation, and social media are represented in the answer returned.

Classes: Ontology Engineering Fall 2018

The number of people living with diabetes mellitus is constantly on the rise, from 108 million in 1980 to 422 million in 2014. And it’ll be the seventh leading cause of death in 2030. The need to rapidly and effectively diagnose and treat the illness is crucial. Recommendations in authoritative literature, Clinical Practice Guidelines (CPG)’s are often tailored to a diverse populations, but as patients get more complex they might not align well with supporting evidence.

Classes: Ontology Engineering Fall 2018

Co-Investigators: Jon Harris, Manling Li, Theo Lipeles, Nasir Pauldon-Collins, Ananya Subburathinam

Classes: Ontology Engineering Fall 2018


Machine learning allows us to learn a model for a given task such as facial recognition with a high degree of accuracy. However, after these models are generated they are often treated as black boxes and the limitations of a model are often unknown to the end user. To address this issue, we’ve developed a semantically enabled system that allows users to explore the limits of a facial recognition model.

Classes: Ontology Engineering Spring 2017

We live in a world that contains many inexpensive, artificial and harmful things, and the packaged food industry is no exception. As many humans consume packaged food, the impact this can be significant.

Classes: Ontology Engineering Spring 2017

The KGES Team:

Project Summary

Welcome! You have found the Knowledge Graph Evaluation System, or KGES. Our goal is to to detect and evaluate inconsistencies or potential incorrect labels from large scale Heterogeneous Knowledge Graphs that is constructed by outputs from IE toolkits.

Classes: Ontology Engineering Spring 2017

Team Members

Hannah De los Santos, Anders Maraviglia


To develop an integrated League of Legends plugin to aid first-time players. This plugin will display suggested builds on screen throughout gameplay.

Classes: Ontology Engineering Spring 2016

Principal Investigators: Zev Battad


Classes: Ontology Engineering Spring 2016

There are many kinds of tea in the world. Even when restricting the word to mean 'real tea', made with the leaves of Camellia sinensis, different kinds of processing give rise to green tea, black tea, white tea, oolong tea, pu-erh tea, and so on. Each of these categories has its own categories, from grassy, sharp sencha green tea to smoky gunpowder green tea. Beyond this, there are many tea blends available – Earl Grey, made from black tea and bergamont, or masala chai, black tea mixed with different spices.

Classes: Ontology Engineering Spring 2016

Use Cases

Conceptual Model

Concept Maps

Here we present maps of the concepts in the tea ontology. These graphics were created using Cmap Tools. Click on any image to see it full-size.


Classes: Ontology Engineering Spring 2016


Chastain, Katherine and Reedy, Cara. "Towards Semantic Tea Blend Recommendations." RPI Technical Report, Ontology Engineering 2016.

Download as a .docx:
"Paper as docx"
Or as a .pdf:
"Paper as pdf"

Presentations done for the Ontology Engineering class in spring 2016

Classes: Ontology Engineering Fall 2018

WhatToMake Course Assignments

This page contains all of the weekly assignments submitted for the Ontology Engineering Course in the process of developing the WhatToMake Application.

Paper Outline

WhatToMake Paper Draft (PDF)