  Researchers in the field of materials science, chemistry, and computational
physics 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 in the scientific process from data
acquisition to data 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 and searchable data
space, simplifying data access and modification through a homogeneous data
interface that is largely agnostic to the data source, i.e., computation or
experiment. The framework's data model is designed to not 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.
