Below, Michelle Borkin answers the second of our three questions.
I think every field is ripe for cross-disciplinary research, but in particular fields that share common broad problems or challenges. For example, with data visualization the specific field of science might be different but the visualization requirements can be very similar. In this case, techniques developed to visualize data in one field can be applied to another field. I have worked for the past few years on one such interdisciplinary collaboration, the Astronomical Medicine project where astronomers and radiologists have come together to solve common multidimensional visualization challenges. One group studies star formation and the other studies human disease diagnosis and treatment, but the raw MRI and telescope data are actually very similar in type, format, size, and noise patterns.
The project has successfully made new astronomical discoveries using sophisticated 3D visualization techniques adapted from the medical field, and has worked to advance visualization and data analysis techniques helping both fields at once! Other common challenges that could connect fields are issues of having large volumes of data requiring data mining techniques, or the common need for specific technologies such as GIS. Everyone should make sure to keep an open mind and ear to other fields of study, and what solutions they are developing no matter how far or seemingly different than their own field of expertise.