As the benefits of Moore's Law diminish, computing performance, and efficiency gains are increasingly achieved through specializing hardware to a domain of computation. However, this limits the hardware's generality and flexibility. Field-programmable gate arrays (FPGAs), microchips which can be reprogrammed to implement arbitrary digital circuits, enable the benefits of specialization while remaining flexible. A challenge to using FPGAs is the complex computer-aided design flow required to efficiently map a computation onto an FPGA. Traditionally, these design flows are closed-source and highly specialized to a particular vendor's devices. We propose an alternate data-driven approach, which uses highly adaptable and retargettable open-source tools to target both commercial and research FPGA architectures. While challenges remain, we believe this approach makes the development of novel and commercial FPGA architectures faster and more accessible. Furthermore, it provides a path forward for industry, academia, and the open-source community to collaborate and combine their resources to advance FPGA technology.