Currently, there is no consistent benchmarking across multi-disciplines. Even no previous work tries to relate different categories of benchmarks in multi-disciplines. This article investigates the origin and evolution of the benchmark term. Five categories of benchmarks are summarized, including measurement standards, standardized data sets with defined properties, representative workloads, representative data sets, and best practices, which widely exist in multi-disciplines. I believe there are two pressing challenges in growing this discipline: establishing consistent benchmarking across multi-disciplines and developing meta-benchmark to measure the benchmarks themselves. I propose establishing benchmark science and engineering; one of the primary goals is to set up a standard benchmark hierarchy across multi-disciplines. It is the right time to launch a multi-disciplinary benchmark, standard, and evaluation journal, TBench, to communicate the state-of-the-art and state-of-the-practice of benchmark science and engineering.