Knowledge Graphs (KGs) have made a qualitative leap and effected a real revolution in knowledge representation. This is leveraged by the underlying structure of the KG which underpins a better comprehension, reasoning and interpretation of knowledge for both human and machine. Therefore, KGs continue to be used as the main means of tackling a plethora of real-life problems in various domains. However, there is no consensus in regard to a plausible and inclusive definition of a domain-specific KG. Further, in conjunction with several limitations and deficiencies, various domain-specific KG construction approaches are far from perfect. This survey is the first to offer a comprehensive definition of a domain-specific KG. Also, the paper presents a thorough review of the state-of-the-art approaches drawn from academic works relevant to seven domains of knowledge. An examination of current approaches reveals a range of limitations and deficiencies. At the same time, uncharted territories on the research map are highlighted to tackle extant issues in the literature and point to directions for future research.

知识图谱（KGs）发生了质的飞跃，并在知识表示方面进行了一次真正的革命。KG的基础结构充分利用了这一基础，可更好地理解，推理和解释人与机器的知识。因此，KG继续被用作解决各种领域中大量现实生活问题的主要手段。但是，关于域特定KG的合理和包容性定义尚无共识。此外，结合一些限制和不足，各种特定于域的KG构建方法远非完美。这项调查是第一个对特定领域的KG进行全面定义的调查。还，本文全面回顾了从与七个知识领域相关的学术著作中得出的最新方法。对当前方法的检查揭示了一系列局限性和不足。同时，突出显示了研究地图上的未知领域，以解决文献中的现存问题，并指出未来研究的方向。