Abstract:

[Purpose/Significance] In the contemporary era, which is characterized by digital intelligence, the profound and unprecedented integration of big data analytics and artificial intelligence technologies is fundamentally transforming archival resources. This paradigm-shifting transition transforms traditional, static analog archival records into highly dynamic, interconnected, data-centric digital records. The fundamental transformation of these primary archival management objects triggers an inevitable, multi-dimensional, holistic reconstruction of the prevailing disciplinary paradigm. Consequently, the rigorous conceptualization and structural construction of the "archival data intelligence paradigm" has definitively emerged as a paramount and indispensable research issue for the sustainable development and continuous modernization of archival science. This issue demands meticulous academic scrutiny and strategic foresight. [Method/Process] Grounded firmly in the foundational scientific paradigm theory and meticulously combined with the pre-existing theoretical frameworks of the archival science paradigm, this comprehensive study methodically explores and elucidates the evolutionary lineage and underlying historical logic of the discipline. Through rigorous systematic literature reviews, advanced conceptual model construction, and cross-disciplinary theoretical integration, this research systematically traces the epistemological and methodological trajectory of the archival science paradigm. It provides a critical analysis of the transformative journey from the paradigm of traditional archival documents and historical materials, to the transitional paradigm of archival information resources, and finally to the cutting-edge, technology-driven paradigm of archival data intelligence. [Results/Conclusions] The newly articulated archival data intelligence paradigm intrinsically positions archival digital intelligence as its fundamental operational core. It is powerfully propelled by the dual interactive engines of data element empowerment and artificial intelligence augmentation. Within this sophisticated architectural framework, the "smart archive" functions as the central cognitive brain, meticulously driven by robust computing power hubs and advanced algorithmic machine-learning models, while being reliably supported by the continuous curation of high-quality, machine-readable archival datasets. This synergistic integration fundamentally culminates in a comprehensive theoretical knowledge framework and a robust practical development system, seamlessly synthesizing digital intelligence culture, innovative technologies, specialized talent cultivation, and adaptive administrative management strategies. Furthermore, by rigorously deconstructing the complex theoretical implications of this novel paradigm and firmly grounding it in both profound philosophical foundations and empirical practical development, this study systematically delineates a holistic structural landscape of the archival data intelligence paradigm. This conceptual landscape is mapped out meticulously across five critical dimensions: ontology (redefining the nature of archival data), epistemology (reconceptualizing how archival knowledge is validated), methodology (innovating analytical approaches), technology (implementing advanced AI architectures), and axiology (reevaluating the inherent societal value of archives). Ultimately, this comprehensive theoretical construct provides invaluable conceptual references and strategic, practical guidance. It actively facilitates the successful digital intelligence transformation and future-proofing of contemporary archival institutions and the broader archival profession worldwide.

Key words: digital intelligence era, archival data, intelligent paradigm, digital intelligence empowerment, graph construction, data element