As a flagship event in the DH community, the digital humanities awards (DHA, http://dhawards.org/) features a wide range of DH projects with broad scope and diverse cases. Since its establishment in 2012, nearly 40 countries have had DH projects nominated for the DHA awards, demonstrating its global engagement. This makes DHA projects a valuable dataset for researching international practices in digital humanities. Resources in any language or format, including those focused on historical and cultural resource development, are eligible for nomination. The awards span various categories, such as best DH tool or suite of tools, best DH data visualisation, best DH blog post or series of posts, and best DH dataset. Notably, recipients of the best DH data visualization award are comprehensive DH projects implemented in real-world contexts, making them more suitable as cases for this research. Out of the 77 projects acknowledged in this category over the past five years (2019-2023), we have selected 34 that specifically focus on developing historical and cultural resources for content analysis.

The selection criteria were: (1) involvement in historical and cultural resource development; (2) ongoing project operation; (3) accessible website and publicly available project-specific information. The selected projects are highly representative in three aspects. Source-wise, they span 16 countries, including Australia, China, the United States, and Italy, and so on. Form-wise, they encompass both tangible and intangible historical and cultural resources. Content-wise, they cover a wide range of topics, such as historical sites and regional historical culture, family historical culture, folk tales, poetry, literature, religion, and historical artifacts (including antiques, maps, manuscripts, old newspapers, handicrafts, among others).

These projects provide a comprehensive overview of how DH approaches are applied to historical and cultural resource development on an international scale. They showcase a diverse range of DH approaches across key domains, such as project management, data processing, and user interaction. Through a detailed content analysis of these initiatives, we can more effectively evaluate the role and impact of DH methodologies in advancing the development of historical and cultural resources.

We acknowledge that our selected cases consist exclusively of award-winning and nominated projects from the DHA, which are determined by public voting. This may introduce a selection bias, as the awards may not fully reflect project quality, but they do promote greater diversity.

To evaluate the role of DH approaches in historical and cultural resource development, it is essential to address a general methodological issue in digital humanities: How do we transition from the digital to meaning? (Rodríguez Díaz, Karines, Haber Guerra, Yamile, & Gómez Masjuán, Miguel Ernesto, 2021). In this study, we employ the input-process-output (IPO) model, a key framework in systems theory, to structure the evaluation of this transition. The IPO model is defined as ‘inputs that lead to processes that in turn lead to outcomes’ (Ilgen, Hollenbeck, Johnson, & Jundt, 2005).

Based on this model and tailored to the context of historical and cultural resource development, we propose the source-transformation-result (STR) framework to guide our content analysis (see Fig. 1). In this framework, the source (input) refers to the raw material for development, which we analyze primarily in terms of their content, form, and quantity. The transformation (process) involves methods adopted to convert these materials into meaningful outputs, and we mainly focus on the digital technologies and techniques used in this process. The result (output) represents the outcomes generated, such as visualizations, new knowledge, or interactive experiences. Unlike traditional IPO models, the STR framework is cyclical. The knowledge generated (e.g., semantic networks or interactive timeline) can feedback into the source phase, influencing future outputs.

The STR framework enables a comprehensive evaluation of how DH approaches impact each stage of historical and cultural resource development.

DH approaches transcend mere technical advancements, embodying a paradigm shift in how we perceive, analyse, and engage with historical and cultural resources. By analysing DH projects through the STR framework, we elucidate several key advantages these approaches offer:

Firstly, at the source end, DH methodologies integrate data from multiple sources, facilitating the regeneration of rich, multifaceted knowledge. This shift from individual to collective analysis enables sophisticated techniques such as cross-textual comparisons and thematic studies, deepening our understanding of historical and cultural dynamics (Champion, 2016; Pacheco, 2022). Additionally, collective analysis dismantles traditional resource silos, promoting a more inclusive and comprehensive historical narrative.

Secondly, the computational techniques central to DH approaches, such as remote reading, empower scholars to analyse vast datasets with unprecedented scale and precision. Utilizing these techniques allows for identifying historical trends, simulating cultural shifts, and reconstructing incomplete datasets, thereby providing new perspectives and insights into previously inaccessible historical phenomena.

Thirdly, interactive, and visual presentations revolutionize the experience and comprehension of history and culture. Tools like dynamic maps, timelines, network diagrams, and 3D models enhance user engagement by enabling interactive exploration of complex historical and cultural contexts. These visualizations transform data presentation into immersive narratives and offer novel interpretations of original resources.

While DH approaches offer numerous benefits for the development of historical and cultural resources, they also bring about some limitations and challenges:

Firstly, the deconstruction and reorganization of corpora through DH methodologies may strip away historical and cultural resources’ unique details and contextual richness. For instance, analysing historical letters or diaries for thematic frequency may result in losing emotional depth and personal context embedded within individual documents. The shift from a nuanced perspective to a generalized one can lead to homogenization, overshadowing the rich diversity of cultural expressions and the voices of minority communities. Such processes raise ethical concerns about representation and the preservation of cultural heritage, as the unique stories of underrepresented groups may be subsumed within dominant narratives.

Secondly, although computational technologies and techniques help generate new knowledge due to their unpredictable behavior when handling large datasets (Rodighiero, Derry, Duhaime, et al., 2022), they have limitations regarding depth of interpretation. Historical and cultural resource development often requires understanding subtleties like linguistic style, cultural references, and historical context — areas where computational tools are not yet adept. This limitation is particularly pronounced when dealing with non-English or indigenous texts, where cultural nuances and linguistic intricacies are critical for meaningful interpretation.

Thirdly, while interactive visual representations enhance user engagement, they may oversimplify complex data for ease of use, leading to reductive interpretations of historical and cultural narratives. Visual tools often prioritize clarity and accessibility, which can result in omitting critical details that are less visually striking or harder to quantify. Furthermore, the emphasis on visual engagement may inadvertently prioritize form over substance, where the aesthetic appeal of visualizations takes precedence over their analytical rigor. This challenge underscores the importance of balancing accessibility with accuracy, ensuring that interactive tools serve as gateways to deeper exploration rather than mere endpoints.