The objective of the Cinema Web Interface is to allow scientists to query image databases by leveraging the metadata associated with the images. Scientists sometimes need to examine specific aspects of the image database for scientific analysis. For example, a climate scientist may want to closely study the ocean flow properties only for one particular time step. The scientist can use the web interface and query using the time step of interest and fetch all the relevant images from the Cinema database for the purpose of analysis. The metadata search involves looking up the properties associated with the images using queries and also further enables refining of the search results by using the groupings associated with the different image clusters. K-means clustering, a machine learning algorithm, groups the images in the Cinema database based on one or more physical variables such as temperature, pressure or salinity among others. This allows the scientist to recognize the underlying groups produced by the data set and the features associated with each group. As an example, a scientist can look up the images aligned with a specific orientation (e.g. theta=90 and phi>0) and then further refine the search result by looking up only the high temperature clusters, which satisfy the query condition.  The web interface is hosted on a webserver with the front-end built using AngularJS and the backend being a restful web service.
