历史地图知识组织:需求、框架及实践

Historical Maps Knowledge Organization:Need,Framework and Practice

历史地图是信息的重要载体之一,其信息隐含在由多种元素组成的复杂网络中。为了高效发挥历史地图的地理空间表示作用,深入挖掘其历史价值、人文价值与证据价值,需要构建统一的历史地图知识组织框架与语义组织模型。本文从形态描述需求、内容描述需求、地理知识服务、文化知识服务、证据知识服务五个维度对历史地图的服务目标进行系统分析,获得“读图者”与“资源管理者”对历史地图的知识组织需求。在此基础上,设计了包含历史地图文本化、概念识别、本体构建以及知识关联路径与关联模式等核心环节的历史地图知识组织框架,并阐述各环节及其之间的核心含义与逻辑关系,形成了历史地图的结构化、数据化、语义化组织机制。本研究为历史地图提供了完整的语义描述范式,丰富了多源异构信息载体的知识组织理论与方法。

Historical maps are one of the important carriers of information,and their information is implicit in a complex network composed of multiple elements.In order to effectively play the geographical spatial representation role of historical maps and deeply explore their historical,humanistic and evidential values,it is necessary to propose a unified historical maps knowledge organization framework and semantic organization model.This paper systematically analyzes the service goals of historical maps from five dimensions:morphological description needs,content description needs,geographical knowledge services,cultural knowledge services,and evidence knowledge services,and obtains the understanding of historical maps by“map readers”and“resource managers”.On this basis,a historical maps knowledge organization framework was designed that includes core links such as historical maps textualization,concept identification,ontology construction,and knowledge association paths and patterns.It also elaborated on each link and the core meanings and logical relationships between them.A structured,data-based,and semantic organization mechanism for historical maps has been formed.The research provides a complete semantic description paradigm for historical maps and enriches the knowledge organization theory and methodology for multi-source heterogeneous information carriers.In the future,it is still necessary to strengthen the automatic generation method of historical maps structured text based on deep learning to improve the efficiency of textualization.Meanwhile,we should expand the association from traditional resources such as documents and images to new resources such as oral history,social medias,knowledge maps,VR to achieve the multi-modal knowledge association of historical maps.