A Workflow Model for Holistic Data Management and Semantic Interoperability in Quantitative Archival Research

TL;DR

This paper introduces a comprehensive, provenance-aware workflow model for managing and integrating archival data into semantic networks, enhancing reproducibility and long-term usability in historical research.

Contribution

It presents a novel holistic workflow for archival data management that emphasizes semantic interoperability and provenance tracking, with practical implementation and application in maritime history.

Findings

Workflow improves data integration and exploration

Enhances provenance tracking and data quality

Supports sustainable, long-term archival research

Abstract

Archival research is a complicated task that involves several diverse activities for the extraction of evidence and knowledge from a set of archival documents. The involved activities are usually unconnected, in terms of data connection and flow, making difficult their recursive revision and execution, as well as the inspection of provenance information at data element level. This paper proposes a workflow model for holistic data management in archival research; from transcribing and documenting a set of archival documents, to curating the transcribed data, integrating it to a rich semantic network (knowledge graph), and then exploring the integrated data quantitatively. The workflow is provenance-aware, highly-recursive and focuses on semantic interoperability, aiming at the production of sustainable data of high value and long-term validity. We provide implementation details for each step of the workflow and present its application in maritime history research. We also discuss relevant quality aspects and lessons learned from its application in a real context.