COSMOS soil moisture sensors provide meso-scale area-averaged soil moisture estimates, presenting a unique opportunity for validating remotely sensed soil moisture data from satellite sensing platforms such as SMAP. New, roving COSMOS sensors can provide greater spatial coverage than their stationary counterparts. However, COSMOS sensors require careful site-specific calibrations, which are not available for roving sensors. As such, it is critically important for researchers to monitor roving COSMOS collection campaigns in near-real-time. However, specialized user interfaces are needed for rapid analysis. Moreover, harmonizing remotely sensed data (such as Landsat, SSURGO, MODIS, SMAP, and SRTM) with a roving COSMOS sensor is non-trivial and requires great care that cannot be accomplished on-the-fly in the field. To address these problems, we are developing the open source SoilMAP (Soil Moisture Analysis and Processing) software, which is a specialized analysis application for COSMOS and SMAP soil moisture data. We are developing this application using PODPAC (https://podpac.org/), a cloud-ready open source Python library for large-scale analysis and on-demand processing of raw earth science data. Our soil moisture analysis application aims to provide (1) customizable, rapid, near-real-time visualization and analysis of COSMOS and SMAP data; (2) unified data access and automated data wrangling to harmonize roving COSMOS measurements and SMAP L3 data; and (3) a streamlined workflow for developing roving COSMOS sensor calibrations with uncertainty estimates. We will demonstrate on-demand processing of raw soil moisture data retrieved from COSMOS sensors and SMAP L3 data using our SoilMAP software framework. We will also show our user workflows specialized for (1) staging data from various remotely-sensed and in-situ sensors, (2) monitoring a COSMOS data collection campaign in near-real-time, and (3) analyzing the resultant data with comparison to SMAP soil moisture. We will outline the steps required to build and customize this application. SoilMAP greatly reduces the burden of analyzing, comparing, and validating soil moisture data using measurements from roving COSMOS sensors.