The projects this year were terrific, showing creativity and thoughtful design. The TAs and I thoroughly enjoyed the presentations, and say kudos to all of you for the great work!"

- Susan B. Davidson

Congratulations!

Students of the Fall 2016 Database and Information Systems (CIS 450/550) class were given a data set of Summer Olympics and were asked to use additional data sources to come up with inventive and interesting projects that explored database concepts learned in the course combined with basic web development, to produce a web app using the data. Developing the project exercised schema design, view based access control, cloud hosting, SQL queries, and performance considerations. They were also directed to use cloud storage with support provided by an AWS in Education Grant award.

The tools, languages and databases used included Oracle, MySQL, MongoDB, DynamoDB, Django, AJAX, Java, Python, Twitter Boostrap, Jade, JQuery, JavaScript, Rails, Flask, Node.js and others. Students also integrated various available APIs such as Google Maps and Places, Facebook, Bing, QRCode, GeoCode Service and Twilio. All in all, there were some terrific projects, and some that were even better than others.

To recognize especially noteworthy projects, we have three special recognitions (Best Demo, Most Creative, Most Whimsical), and chose a best of each TA group. Here are our picks!

Best Demo

Group 18

This group created a web application that provides profile information of Olympic athletes in a virtual collectible card game platform. Users are asked a series of dynamically generated trivia questions based on random queries to earn athlete cards, the card collection is bound to the user’s account and may be browsed on demand. This group used a diverse collection of datasets from The Guardian (csv), Sports Reference (html), and Wikipedia (html).

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Most Creative

Group 16

This group used the the Million Song Dataset, which includes data on similarities between songs, song play counts (as determined by trends on Last.fm, a music streaming service), genre classifications of songs, and many more types of data. They wanted to make an application that let users visualize relationships between songs, artists, genres, and more. The Song Engine lets users do all of this with beautiful visualizations.

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Most Whimsical

Group 32 - Olympic Athletes VS Pokemon

Because of the exciting Olympics Game in the summer of 2016 and the recent popularity of Pokemon GO , this group decided to design and develop a web application that can match Olympics athletes with Pokemon. For each athlete, the app will find a best matched Pokemon based on his/her sports and number of medals earned. This group also implemented features that match athletes and pokemon based on their popularity. With this data and implementations, the group designed two small games:
(1) users can compare and guess which pokemon will win a battle, and
(2) choose one pokemon out of four to match with an athlete.

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Best Projects under each T.A.

Group 6 (Tengyuan)

This group created a website on which users could search through doping scandals and compare data across different years and countries, provide some additional analysis like correlation of number of scandals with Corruption Perceptions Index.

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Group 9 (Shreya)

This team created an application that provides users the ability to analyze the impact of geographic, demographic, and economic variables on Olympic medalists in visually engaging and informative ways.

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Group 14 (Alex)

This group created a wikipedia-like application for Olympics, titled Olympedia, which aims at providing all the information one could possibly need, either for the Summer Olympics or for the Winter Olympics. Using Olympedia all the possible queries for the current Olympics or any Olympics in the history of the event can be answered. This information can then be visualized using a graph which makes the information easier to understand.

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Group 18 (Mani)

This group created a web application that provides profile information of Olympic athletes in a virtual collectible card game platform. Users are asked a series of dynamically generated trivia questions based on random queries to earn athlete cards, the card collection is bound to the user’s account and may be browsed on demand. This group used a diverse collection of datasets from The Guardian (csv), Sports Reference (html), and Wikipedia (html).

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Group 27 (Wei)

This group implemented a quiz application which shall help the user to explore olympic data over time. This particular application is designed to help teachers evaluate and assess the performance of all the students in a class. The student can view his learning curve on a topic assigned by the teacher. We have tried to maximize the amount of learning for a given topic by incorporating bing search on the questions and interesting facts.

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Group 30 - Olympicpedia (Yunwen)

Olympicpedia consists of four major features/components: world maps to visualize the data, quiz to test user's knowledge, table views to summarize the user's interest, and an API to offer additional choices. World maps and table views are built up with relational database and MySql, and the quiz is based on NoSql and DynamoDB.

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