Abstract
Recently, collection and accumulation of various types of data are much easier than ever, yielding many kinds of so-called big data. In particular, as the global market of wearable devices is expected to grow rapidly and they are suitable for measuring biological signals non-invasively for a long period of time, utilizations of big biological data corrected by those devices are envisioned extensively in many fields. However, extracting information from big biological data corrected via multiple wearable devices may become burdensome as each device produces its own data in a unique format. In the current study, we developed a software environment to support handling and analyses of a large amount of data, employing the accumulated knowledge of data science. Further, we implemented a GUI application on top of this environment. The application provides an integrated platform for management of experimental data and conditions, data analyses, and visualization of analyzed data. The application was developed in Python, considering its high extensibilities by other users and availability in many platform such as Windows, Mac OSX and Linux, and thereby planned to open to the public.
