Researchers in the field of computational physics, chemistry, and materials
science are regularly posed with the challenge of managing large and
heterogeneous data spaces. The amount of data increases in lockstep with
computational efficiency multiplied by the amount of available computational
resources, which shifts the bottleneck within the scientific process from data
acquisition to data post-processing and analysis. We present a framework
designed to aid in the integration of various specialized data formats, tools
and workflows. The signac framework provides all basic components required to
create a well-defined and thus collectively accessible data space, simplifying
data access and modification through a homogeneous data interface, largely
agnostic of the data source, i.e., computation or experiment. The framework's
data model is designed not to require absolute commitment to the presented
implementation, simplifying adaption into existing data sets and workflows.
This approach not only increases the efficiency with which scientific results
can be produced, but also significantly lowers barriers for collaborations
requiring shared data access.