The goal of the course with this project was to create a encyclopedic information resource of a complicated domain to facilitate easier and a more comprehensive understanding of the domain presented.
The artifact should provide overview and detail, with appropriate use of design strategies, such as well chosen labeling and tagging, use of standard nomenclatures where appropriate, semantic segmentation at multiple levels of granularity, and meaningful juxtaposition of information. The artifact should combine multiple sources and media types. It should also provide participatory features such as filtering, navigating, tagging, and/or contributing information.
Although daily news may not be a complex domain to a regular reader, there could be a few scenarios when the reader is unable to understand the information provided in its entirety. Possible few such scenarios could be,
The idea is to use the affordances of the digital media exploring the possibility of using visualizations, spatial presentation of news on a geographical map, affinity and alliance graphs, time-lines and others techniques and aids to enhance the comprehension of the news articles.
The early stages involved extensive analysis of other similar products in the market, including Flipboard, Feedly, News360, etc. The salient features strengths and limitations of each of the product was marked on an affordance grid and a set of ideal features for the product to be designed was made.
Based on the exploratory study the following were identified as the key stones around which the artifact was to be designed.
The meta-information related with a news article were broken down and each of them was supplemented with visualization or a filtering mechanism that would provide a flexible navigation / filtering to the reader.
With the above mentioned guides, the wireframe mockup of the news reader was created and think-aloud technique was used with 6 participants to receive early feedback and design the iterations.
The concept was prototyped reading RSS Feeds from News Sources and using Textalytics API to extract meta-data like location, people from the articles. The tags and meta-data were stored in a MySQL DB and the front end was rendered on the browser using Google Map API for showing different origins of news articles.
The demonstration was limited to 3 of the 7 meta-information.