"Reproducible research has been recognized as a growing concern in most areas of science. To achieve widespread adoption of repeatable, transparent research practices, some commentators have identified a need for better software for authoring reproducible digital publications. Complicating this goal, scientific investigations increasingly involve interdisciplinary teams, sophisticated workflows for acquiring and analyzing data, and huge datasets that rely on considerable metadata to interpret. Computational scientists have begun to adopt tools for managing the complex histories of their data and procedures, but software which simultaneously allows researchers to specify experiments, remotely control equipment, and capture and organize data remains immature. This thesis demonstrates a software architecture for programmable remote control of custom and commercial lab equipment, automatic annotation and queryable storage of data sets, and provenance-aware specification of experiment and analysis procedures. The design consists of a suite of small, single-purpose software services which may be controlled remotely from a web browser, including a graphical programming tool, an abstraction layer for interfacing with commercial and custom embedded systems, and a hybrid document/table database for persistent storage of annotated experimental data. The software implementation embraces modern web technologies and best practices to produce a modular, user-extensible framework that is well-suited for helping to integrate computer-controlled research labs with the emerging Internet of Things."--Page ii.
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