  The ever-growing datasets in observational astronomy have challenged
scientists in many aspects, including an efficient and interactive data
exploration and visualization. Many tools have been developed to confront this
challenge. However, they usually focus on displaying the actual images or focus
on visualizing patterns within catalogs in a predefined way. In this paper we
introduce Vizic, a Python visualization library that builds the connection
between images and catalogs through an interactive map of the sky region. Vizic
visualizes catalog data over a custom background canvas using the shape, size
and orientation of each object in the catalog. The displayed objects in the map
are highly interactive and customizable comparing to those in the images. These
objects can be filtered by or colored by their properties, such as redshift and
magnitude. They also can be sub-selected using a lasso-like tool for further
analysis using standard Python functions from inside a Jupyter notebook.
Furthermore, Vizic allows custom overlays to be appended dynamically on top of
the sky map. We have initially implemented several overlays, namely, Voronoi,
Delaunay, Minimum Spanning Tree and HEALPix grid layers, which are helpful for
visualizing large-scale structure. All these overlays can be generated, added
or removed interactively with one line of code. The catalog data is stored in a
non-relational database, and the interfaces were developed in JavaScript and
Python to work within Jupyter Notebook, which allows to create custom widgets,
user generated scripts to analyze and plot the data selected/displayed in the
interactive map. This unique design makes Vizic a very powerful and flexible
interactive analysis tool. Vizic can be adopted in variety of exercises, for
example, data inspection, clustering analysis, galaxy alignment studies,
outlier identification or simply large-scale visualizations.
