The Problem
Museum databases are flat and one-dimensional. There is no way to quantify the things people feel while looking at, or experiencing, art. This flatness makes it difficult to connect people with artwork based on hard-to-articulate themes (such as feelings).
Our Approach
We have decided to try and use the responses people have to artwork in order to add depth to museum data files. We want to show the “texture and personality” of a collection, and the way exhibits make people feel.
The base for this project is Landon’s emotional responses to art project proposal. Our product development is inspired by a combination of Kenneth’s idea of categorizing art by keywords, Chris’s guided tour concept, and our desire to connect people with artwork that resonates with them. We intend to quantify the museum experience, then use that data for two things.
- First, we will deepen the existing museum database by adding user experiences.
- Second, we want to use this data to recommend art to people based on themes, emotions, and related pieces.
Our product could allow for art experts to discuss the relationship between certain techniques and the reactions viewers have, or provide people a way to search for artwork based on feeling and then share that via Instagram or Snapchat. It should be built in a way that is easy to access and navigate, protects individual data, and can be easily tied to existing habits (in example: social media integration or sharing).
Our vision is to create an application that will allow people to search for art based on emotions and feelings. Our current plan is to help people who are bad at being romantic or expressing their feelings, be better at it through artwork.