Evaluatology: The Science and Engineering of Evaluation
<|reference_start|>Evaluatology: The Science and Engineering of Evaluation: Evaluation is a crucial aspect of human existence and plays a vital role in various fields. However, it is often approached in an empirical and ad-hoc manner, lacking consensus on universal concepts, terminologies, theories, and methodologies. This lack of agreement has significant repercussions. This article aims to formally introduce the discipline of evaluatology, which encompasses the science and engineering of evaluation. We propose a universal framework for evaluation, encompassing concepts, terminologies, theories, and methodologies that can be applied across various disciplines.   Our research reveals that the essence of evaluation lies in conducting experiments that intentionally apply a well-defined evaluation condition to diverse subjects and infer the impact of different subjects by measuring and/or testing. Derived from the essence of evaluation, we propose five axioms focusing on key aspects of evaluation outcomes as the foundational evaluation theory. These axioms serve as the bedrock upon which we build universal evaluation theories and methodologies. When evaluating a single subject, it is crucial to create evaluation conditions with different levels of equivalency. By applying these conditions to diverse subjects, we can establish reference evaluation models. These models allow us to alter a single independent variable at a time while keeping all other variables as controls. When evaluating complex scenarios, the key lies in establishing a series of evaluation models that maintain transitivity. Building upon the science of evaluation, we propose a formal definition of a benchmark as a simplified and sampled evaluation condition that guarantees different levels of equivalency. This concept serves as the cornerstone for a universal benchmark-based engineering approach to evaluation across various disciplines, which we refer to as benchmarkology.<|reference_end|>
@article{zhan2024evaluatology:,
    title={Evaluatology: The Science and Engineering of Evaluation},
    author={Jianfeng Zhan, Lei Wang, Wanling Gao, Hongxiao Li, Chenxi Wang, Yunyou
  Huang, Yatao Li, Zhengxin Yang, Guoxin Kang, Chunjie Luo, Hainan Ye, Shaopeng
  Dai, Zhifei Zhang},
    journal={arXiv preprint arXiv:2404.00021},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.00021},
    primaryClass={cs.HC cs.CE cs.CY cs.PF}
}