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Digital humanities database is one of the essential tools in digital humanities research area. Therefore, examining the usage of digital humanities database in academic papers is conducive to assessing the value of digital humanities database for scientific research activities and improving the construction of digital humanities infrastructure.

This paper constructs an evaluation system of digital humanities database from the perspective of academic influence and social influence, with mention frequency, usage motivation, platform access data, usage region and usage discipline as indicators and takes China Biographical Database Project as the empirical object to explore the usage of digital humanities database in China.

The data analysis result demonstrates that digital humanities databases are widely used and recognized in China. However, the problem of low actual usage remains.

This paper constructs the digital humanistic database's evaluation system and discusses applying the digital humanistic database in China, which provides a new perspective and method for the influence evaluation study of the digital humanistic database.

Digital humanities aim to use a digital-based revolutionary new way to carry out enhanced forms of humanities research more effectively and efficiently. This study develops a character social network relationship map tool (CSNRMT) that can semi-automatically assist digital humanists through human-computer interaction to more efficiently and accurately explore the character social network relationships from Chinese ancient texts for useful research findings.

With a counterbalanced design, semi-structured in-depth interview, and lag sequential analysis, a total of 21 research subjects participated in an experiment to examine the system effectiveness and technology acceptance of adopting the ancient book digital humanities research platform with and without the CSNRMT to interpret the characters and character social network relationships.

The experimental results reveal that the experimental group with the CSNRMT support appears higher system effectiveness on the interpretation of characters and character social network relationships than the control group without the CSNRMT, but does not achieve a statistically significant difference. Encouragingly, the experimental group with the CSNRMT support presents remarkably higher technology acceptance than the control group without the CSNRMT. Furthermore, use behaviors analyzed by lag sequential analysis reveal that the CSNRMT could assist digital humanists in the interpretation of character social network relationships. The results of the interview present positive opinions on the integration of system interface, smoothness of operation, and external search function.

Currently, the system effectiveness of exploring the character social network relationships from texts for useful research findings by using the CSNRMT developed in this study will be significantly affected by the accuracy of recognizing character names and character social network relationships from Chinese ancient texts. The developed CSNRMT will be more practical when the offered information about character names and character social network relationships is more accurate and broad.

This study develops an ancient book digital humanities research platform with an emerging CSNRMT that provides an easy-to-use real-time interaction interface to semi-automatically support digital humanists to perform digital humanities research with the need of exploring character social network relationships.

At present, a real-time social network analysis tool to provide a friendly interaction interface and effectively assist digital humanists in the digital humanities research with character social networks analysis is still lacked. This study thus presents the CSNRMT that can semi-automatically identify character names from Chinese ancient texts and provide an easy-to-use real-time interaction interface for supporting digital humanities research so that digital humanists could more efficiently and accurately establish character social network relationships from the analyzed texts to explore complicated character social networks relationship and find out useful research findings.

An automatic text annotation system (ATAS) that can collect resources from different databases through Linked Data (LD) for automatically annotating ancient texts was developed in this study to support digital humanities research. It allows the humanists referring to resources from diverse databases when interpreting ancient texts as well as provides a friendly text annotation reader for humanists interpreting ancient text through reading. The paper aims to discuss whether the ATAS is helpful to support digital humanities research or not.

Based on the quasi-experimental design, the ATAS developed in this study and MARKUS semi-ATAS were compared whether the significant differences in the reading effectiveness and technology acceptance for supporting humanists interpreting ancient text of the Ming dynasty’s collections existed or not. Additionally, lag sequential analysis was also used to analyze users’ operation behaviors on the ATAS. A semi-structured in-depth interview was also applied to understand users’ opinions and perception of using the ATAS to interpret ancient texts through reading.

The experimental results reveal that the ATAS has higher reading effectiveness than MARKUS semi-ATAS, but not reaching the statistically significant difference. The technology acceptance of the ATAS is significantly higher than that of MARKUS semi-ATAS. Particularly, the function comparison of the two systems shows that the ATAS presents more perceived ease of use on the functions of term search, connection to source websites and adding annotation than MARKUS semi-ATAS. Furthermore, the reading interface of ATAS is simple and understandable and is more suitable for reading than MARKUS semi-ATAS. Among all the considered LD sources, Moedict, which is an online Chinese dictionary, was confirmed as the most helpful one.

This study adopted Jieba Chinese parser to perform the word segmentation process based on a parser lexicon for the Chinese ancient texts of the Ming dynasty’s collections. The accuracy of word segmentation to a lexicon-based Chinese parser is limited due to ignoring the grammar and semantics of ancient texts. Moreover, the original parser lexicon used in Jieba Chinese parser only contains the modern words. This will reduce the accuracy of word segmentation for Chinese ancient texts. The two limitations that affect Jieba Chinese parser to correctly perform the word segmentation process for Chinese ancient texts will significantly affect the effectiveness of using ATAS to support digital humanities research. This study thus proposed a practicable scheme by adding new terms into the parser lexicon based on humanists’ self-judgment to improve the accuracy of word segmentation of Jieba Chinese parser.

Although some digital humanities platforms have been successfully developed to support digital humanities research for humanists, most of them have still not provided a friendly digital reading environment to support humanists on interpreting texts. For this reason, this study developed an ATAS that can automatically retrieve LD sources from different databases on the Internet to supply rich annotation information on reading texts to help humanists interpret texts. This study brings digital humanities research to a new ground.

This study proposed a novel ATAS that can automatically annotate useful information on an ancient text to increase the readability of the ancient text based on LD sources from different databases, thus helping humanists obtain a deeper and broader understanding in the ancient text. Currently, there is no this kind of tool developed for humanists to support digital humanities research.

With the rapid development of digital humanities, some digital humanities platforms have been successfully developed to support digital humanities research for humanists. However, most of them have still not provided a friendly digital reading environment and practicable social network analysis tool to support humanists on interpreting texts and exploring characters’ social network relationships. Moreover, the advancement of digitization technologies for the retrieval and use of Chinese ancient books is arising an unprecedented challenge and opportunity. For these reasons, this paper aims to present a Chinese ancient books digital humanities research platform (CABDHRP) to support historical China studies. In addition to providing digital archives, digital reading, basic search and advanced search functions for Chinese ancient books, this platform still provides two novel functions that can more effectively support digital humanities research, including an automatic text annotation system (ATAS) for interpreting texts and a character social network relationship map tool (CSNRMT) for exploring characters’ social network relationships.

This study adopted DSpace, an open-source institutional repository system, to serve as a digital archives system for archiving scanned images, metadata, and full texts to develop the CABDHRP for supporting digital humanities (DH) research. Moreover, the ATAS developed in the CABDHRP used the Node.js framework to implement the system’s front- and back-end services, as well as application programming interfaces (APIs) provided by different databases, such as China Biographical Database (CBDB) and TGAZ, used to retrieve the useful linked data (LD) sources for interpreting ancient texts. Also, Neo4j which is an open-source graph database management system was used to implement the CSNRMT of the CABDHRP. Finally, JavaScript and jQuery were applied to develop a monitoring program embedded in the CABDHRP to record the use processes from humanists based on xAPI (experience API). To understand the research participants’ perception when interpreting the historical texts and characters’ social network relationships with the support of ATAS and CSNRMT, semi-structured interviews with 21 research participants were conducted.

An ATAS embedded in the reading interface of CABDHRP can collect resources from different databases through LD for automatically annotating ancient texts to support digital humanities research. It allows the humanists to refer to resources from diverse databases when interpreting ancient texts, as well as provides a friendly text annotation reader for humanists to interpret ancient text through reading. Additionally, the CSNRMT provided by the CABDHRP can semi-automatically identify characters’ names based on Chinese word segmentation technology and humanists’ support to confirm and analyze characters’ social network relationships from Chinese ancient books based on visualizing characters’ social networks as a knowledge graph. The CABDHRP not only can stimulate humanists to explore new viewpoints in a humanistic research, but also can promote the public to emerge the learning interest and awareness of Chinese ancient books.

This study proposed a novel CABDHRP that provides the advanced features, including the automatic word segmentation of Chinese text, automatic Chinese text annotation, semi-automatic character social network analysis and user behavior analysis, that are different from other existed digital humanities platforms. Currently, there is no this kind of digital humanities platform developed for humanists to support digital humanities research.

Digital humanities research platform for biographies of Malaysia personalities (DHRP-BMP) was collaboratively developed by the Research Center for Chinese Cultural Subjectivity in Taiwan, the Federation of Heng Ann Association Malaysia, and the Malaysian Chinese Research Center of Universiti Malaya in this study. Using The Biographies of Malaysia Henghua Personalities as the main archival sources, DHRP-BMP adopted the Omeka S, which is a next-generation Web publishing platform for institutions interested in connecting digital cultural heritage collections with other resources online, as the basic development system of the platform, to develop the functions of close reading and distant reading both combined together as the foundation of its digital humanities tools.

The results of the first-stage development are introduced in this study, and a case study of qualitative analysis is provided to describe the research process by a humanist scholar who used DHRP-BMP to discover the character relationships and contexts hidden in The Biographies of Malaysia Henghua Personalities.

Close reading provided by DHRP-BMP was able to support humanities scholars on comprehending full text contents through a user-friendly reading interface while distant reading developed in DHRP-BMP could assist humanities scholars on interpreting texts from a rather macro perspective through text analysis, with the functions such as keyword search, geographic information and social networks analysis for humanities scholars to master on the character relationships and geographic distribution from personality biographies, thus accelerating their text interpretation efficiency and uncovering the hidden context.

At present, a digital humanities research platform with real-time characters’ relationships analysis tool that can automatically generate visualized character relationship graphs based on Chinese named entity recognition (CNER) and character relationship identification technologies to effectively assist humanities scholars in interpreting characters’ relationships for digital humanities research is still lacking so far. This study thus presents the DHRP-BMP that offers the key features that can automatically identify characters’ names and characters’ relationships from personality biographies and provide a user-friendly visualization interface of characters’ relationships for supporting digital humanities research, so that humanities scholars could more efficiently and accurately explore characters’ relationships from the analyzed texts to explore complicated characters’ relationships and find out useful research findings.

This study aims to extract knowledge of ancient Chinese scientific and technological documents bibliographic summaries (STDBS) and provide the knowledge graph (KG) comprehensively and systematically. By presenting the relationship among content, discipline, and author, this study focuses on providing services for knowledge discovery of ancient Chinese scientific and technological documents.

This study compiles ancient Chinese STDBS and designs a knowledge mining and graph visualization framework. The authors define the summaries' entities, attributes, and relationships for knowledge representation, use deep learning techniques such as BERT-BiLSTM-CRF models and rules for knowledge extraction, unify the representation of entities for knowledge fusion, and use Neo4j and other visualization techniques for KG construction and application. This study presents the generation, distribution, and evolution of ancient Chinese agricultural scientific and technological knowledge in visualization graphs.

The knowledge mining and graph visualization framework is feasible and effective. The BERT-BiLSTM-CRF model has domain adaptability and accuracy. The knowledge generation of ancient Chinese agricultural scientific and technological documents has distinctive time features. The knowledge distribution is uneven and concentrated, mainly concentrated on C1-Planting and cultivation, C2-Silkworm, and C3-Mulberry and water conservancy. The knowledge evolution is apparent, and differentiation and integration coexist.

This study is the first to visually present the knowledge connotation and association of ancient Chinese STDBS. It solves the problems of the lack of in-depth knowledge mining and connotation visualization of ancient Chinese STDBS.

The purpose of this paper is to propose a knowledge extraction framework to extract knowledge, including entities and relationships between them, from unstructured texts in digital humanities (DH).

The proposed cooperative crowdsourcing framework (CCF) uses both human–computer cooperation and crowdsourcing to achieve high-quality and scalable knowledge extraction. CCF integrates active learning with a novel category-based crowdsourcing mechanism to facilitate domain experts labeling and verifying extracted knowledge.

The case study shows that CCF can effectively and efficiently extract knowledge from multi-sourced heterogeneous data in the field of Tang poetry. Specifically, CCF achieves higher accuracy of knowledge extraction than the state-of-the-art methods, the contribution of feedbacks to the training model can be maximized by the active learning mechanism and the proposed category-based crowdsourcing mechanism can scale up the effective human–computer collaboration by considering the specialization of workers in different categories of tasks.

This research proposes CCF to enable high-quality and scalable knowledge extraction in the field of Tang poetry. CCF can be generalized to other fields of DH by introducing domain knowledge and experts.

The extracted knowledge is machine-understandable and can support the research of Tang poetry and knowledge-driven intelligent applications in DH.

CCF is the first human-in-the-loop knowledge extraction framework that integrates active learning and crowdsourcing mechanisms; he human–computer cooperation method uses the feedback of domain experts through the active learning mechanism; the category-based crowdsourcing mechanism considers the matching of categories of DH data and especially of domain experts.

The existing consensus reaching mechanisms ignore the influence of social triangle structure on the decision-makers’ (DMs') weights, and the consensus reaching process (CRP) fails to fully reflect the DMs' subjectivity and can be time consuming and costly. To solve these issues, a novel CRP for multi-criteria group decision-making (MCGDM) problems with intuitionistic grey linguistic numbers (IGLNs) is proposed in this paper.

First, a weight calculation method is proposed by analysing the triangle structure of DMs' social network and scale of adjacent nodes. Then, a consensus degree index based on three-level polygon area is defined and applied to identify the inconsistent DMs. Finally, the feedback mechanism based on particle swarm optimisation (PSO) algorithm under grey linguistic environment is developed, where subjective trust relationships in social network is utilised to determine the adjustment coefficient.

The advantages of the proposed method are highlighted by two practical applications of the evaluation of tunnel construction method and the selection of a hotel for the centralised isolation. Comparision analysis and numerical simulation are performed to reveal the effectiveness and applicability of the method.

The proposed model can not only reflect the effect of triangle structure in social network on DMs' weights, but also reduce the time and cost of decision-making.

The main contribution of this paper is to propose a new MCGDM model based on intuitionistic grey linguistic numbers, which can handle the problem of inconsistency of information more effectively.

There is a wealth of value hidden in regional cultural heritage, but its preservation status is not optimistic. This study introduces a method that focuses on the inherent cultural value of regional cultural heritage to preserve it by value construction and release.

Based on the great value of regional cultural heritage due to spatial adjacency and temporal continuity, this paper focuses on its inherent cultural value to explore the preservation path and chooses Shichahai cultural heritage digital resources for a case study. This paper draws lessons from the narrative method of ancient Chinese historiography, constructs a cultural space and tells cultural stories. A linked data organization model for digital resources is created to construct a conceptual cultural space. Then, the space is materialized by linked dataset creation. The authors tell cultural stories discovered from the space, which are presented by various user interfaces using visualization technologies.

A cultural space promotes the development of a fine-grained description of regional cultural heritage and aids in relationship discovery to enhance the value construction ability. Additionally, storytelling via interactive user interfaces is helpful in the utilization and dissemination of knowledge extracted from a cultural space and enhances the value release of regional cultural heritage. In this way, a path with the inherent cultural value of regional cultural heritage as the core is established, and preservation is achieved.

This study focuses on the inherent cultural value of regional cultural heritage and proposes a new path to preserve these resources. This approach will enrich research on the preservation of regional cultural heritage and contribute to the construction and release of its cultural value.