Graph-based modeling of the bibliographic items and linked open data for the citation records

We present VIVO-ISF ontology-driven modeling of the scholarly works, originally recorded in Symplectic Elements. Initially, we concentrated on the “academic article” category only. For the academic articles, Elements captures the title of the article, list of the persons and their contribution roles (such as authors, editors, translators), journal title, volume number, issue, ISSN, DOI, publication status, pagination etc. - named as “Citation Items”. The data for these citation items may or may not be available in every internal/external data source and may also vary among available data sources. This leads to recording multiple versions of the same academic article - named as “Version Entries”. The version entries of an article are formalized using a graph-based approach. We used attributed graphs. Graphs with node and edge attribution are typed over an attribute type graph (ATG). Attributed graphs (AG) ensure that all edges and nodes of a graph are typed over ATG and each node is either a source or target (or both). We present our graph-based model, outcomes of the analysis of the version entries graph and the process of the merge of the different version entries graph into a single record - known an Uber Record.本研究提出基于VIVO-ISF本体的学术作品建模方法，相关数据最初存储于Symplectic Elements系统中。研究初期，我们仅针对学术期刊论文类别开展建模工作。对于学术期刊论文，Symplectic Elements会采集论文标题、人员列表及其贡献角色（如作者、编辑、译者）、期刊名称、卷号、期号、国际标准连续出版物编号（ISSN）、数字对象唯一标识符（DOI）、出版状态、页码等信息，此类信息被称为“著录项（Citation Items）”。上述著录项的数据并非在所有内部或外部数据源中均可获取，且在不同可用数据源间也可能存在差异，这一情况会导致同一学术期刊论文被记录为多个不同的“版本条目（Version Entries）”。我们采用基于图的方法对论文的版本条目进行形式化建模，具体使用属性图（Attributed Graphs，AG）。带有节点与边属性的图需基于属性类型图（Attribute Type Graph，ATG）完成类型定义。属性图可确保图中所有边与节点均基于ATG完成类型标注，且每个节点均可作为源节点、目标节点，或同时兼具两种角色。本研究展示了所提出的基于图的模型、版本条目图的分析结果，以及将不同版本条目图合并为单条统一记录（Uber Record）的流程。