Challenges and Opportunities for Visual Analytics in Jurisprudence

TL;DR

This work tackles the challenge of applying Visual Analytics to jurisprudence by focusing on the distinct needs of legal reasoning that hinge on tacit knowledge and complex hierarchies. It reports semi-structured interviews with nine legal experts, identifies a three-phase workflow ($W_ exttt{P1}$-$W_ exttt{P3}$) to structure legal analysis, and proposes a VA design that combines data navigation (trees, treemaps, icicle plots), knowledge representation (concept maps, knowledge graphs), and analytical reasoning with provenance. The authors argue for a human-in-the-loop VA approach that externalizes tacit domain knowledge and captures analytical provenance, enabling more transparent, reproducible legal reasoning and more efficient navigation across diverse legal sources. They also present a case study around the Bundespolizeigesetz to illustrate the workflow and discuss design implications, limitations, and generalization to other text-intensive domains. The work lays a foundation for knowledge-assisted VA in law and other domains, offering a blueprint for integrating domain expertise with machine intelligence in a verifiable, scalable manner.

Abstract

Legal exploration, analysis, and interpretation remain complex and demanding tasks, even for experienced legal scholars, due to the domain-specific language, tacit legal concepts, and intentional ambiguities embedded in legal texts. In related, text-based domains, Visual Analytics (VA) has become an indispensable tool for navigating documents, representing knowledge, and supporting analytical reasoning. However, legal scholarship presents distinct challenges: it requires managing formal legal structure, drawing on tacit domain knowledge, and documenting intricate and accurate reasoning processes - needs that current VA system designs for law fail to address adequately. We identify and describe key challenges and underexplored opportunities in applying VA to law, exploring how these technologies might better serve the legal domain. Interviews with nine legal experts reveal that current legal information retrieval interfaces do not adequately support the navigational complexity of law, often forcing users to rely on internalized legal expertise instead. To address this gap, we identify a three-phase workflow for legal experts, which highlights opportunities for VA to support legal reasoning through knowledge externalization and provenance tracking, leveraging tree-, graph-, and hierarchy-based visualizations. Through this contribution, our work establishes a user-centered VA workflow for the legal domain, recognizing tacit legal knowledge as a critical element of sense-making and insight generation, and situates these contributions within a broader research agenda for VA in law and other text-based disciplines.

Figures (3)

• Figure 1: Using Visual Analytics (VA) for legal research can simplify working with diverse legal documents -- including laws, explanatory memoranda, and court rulings -- to support legal scholars in three key tasks: (1) fundamental information retrieval, (2) understanding structural relationships, and (3) advancing legal reasoning, while addressing several challenges. Through interviews with domain experts, we identify three workflow phases, namely (1) Discovery & Scoping, (2) Analysis & Interpretation, and (3) Synthesis & Documentation. Through them, scholars iteratively navigate through and generate analytical artifacts that capture explicit and tacit knowledge, fostering a deeper comprehension of legal structures and reasoning, and informing a VA design for jurisprudence.
• Figure 2: An annotated concept sketch of a legal database's user interface that displays the results for a search query contextualized with VA techniques. On the left-hand side, the user interface (1) displays the formal legal structure of the Bundespolizeigesetz (Federal Police Act). At the center, the database (2) renders the selected legal norm's text with keywords from the query highlighted. On the right-hand side, the user interface (3) lists related documents such as legal norms and law commentaries.
• Figure 3: A mock-up of our proposed Visual Analytics workflow that illustrates the role of Concept Maps, Icicle Plots, and Treemaps in the different phases of the three-phase workflow. Cursors and arrows indicate possible user interactions.