Modeling indoor air quality requires reliable data on pollutant emission rates (ERs) from indoor sources. While many studies focus on measuring indoor pollutant concentrations, far fewer provide the source-specific ERs needed for predictive modeling, and those that do often report fragmented and non-standardized formats that limit their use. This paper addresses this gap by introducing PANDORA (a comPilAtioN of inDOor aiR pollutAnt emissions), an internet-based open-access database designed to improve consistency and transparency in indoor air quality assessments. PANDORA systematically compiles ERs data for gaseous and particulate pollutants from a wide range of indoor sources. It classifies 747 sources into comprehensive categories such as construction and decoration materials (354), furniture (38), cleaning products and air fresheners (123), occupants and occupant activities (134), heating and cooking appliances (48), electrical equipment (40), whole room or building (6) and others (4). In this paper, we summarize key experimental methods used to assess the pollutants. To aid in informed decision-making, statistical analyses are provided for selected indoor pollutants of interest, including PM2.5, formaldehyde, benzene, and TVOC. Additionally, we compare the impact of using three different modeling approaches and assumptions through a case study that uses the PANDORA data to evaluate indoor pollutant ERs in a room. This application shows how PANDORA supports more transparent and consistent use of emission rate data. Our findings highlight that, despite compiling 9968 emission rate entries, expanding PANDORA with new measurements will further strengthen the accuracy and reliability of indoor air quality modeling and exposure assessments.