This paper presents a review of recent research and development on methodologies relevant to automating mapping of points in building control systems and between building control systems and external or replacement software and hardware. Manual point mapping is labor intensive and costly, presenting a major impediment to innovations in building control (e.g., automated fault detection and diagnostics, self-healing, and automated commissioning for existing building control systems). The methods reviewed focus on classifying building control system points, especially sensor classifications by sensor type. Fewer publications address other important aspects of the point mapping problem, such as discovering spatial and functional relationships among points, relationships between control system points, physical systems, and equipment, and between various equipment and the systems of which they are part, and discovering metadata, normalizing it to a common namespace, and assigning the metadata to control system points. To motivate further development of new automated point mapping approaches, we identify many research questions organized into four key technical needs: 1) a complete solution and underlying problem formulation, 2) alignment of methods with the actual point mapping problem, 3) test cases, data sets for testing, explicit test procedures, and consistent performance metrics for reporting testing and evaluation results, and 4) understanding of the applicable data space to ensure future adaptability of automated BAS point mapping.