Humanities disciplines such as history, classical studies, literary studies, and philology have in recent years experienced a “spatial turn” similar to that begun in prior decades within the social sciences and archaeology. Many researchers in these fields are now explicitly recording the spatial and temporal attributes of their data and mapping them for visual analysis and argumentation. In many cases they are also performing spatial or spatial-temporal computations, including but not limited to viewshed, network, and cluster analyses, and agent-based and other models and simulations are increasingly common. The software used for this work is the same as that used for the environmental and social sciences: desktop GIS and specialized spatial and natural language processing libraries for the Python and R languages. These new spatial researchers are experiencing the same representational and analytic challenges in studying geographical dynamics that are well known to other disciplines, but they also face distinctive issues related to the nature of historical humanities data. Furthermore, epistemologies associated with new quantitative approaches must be reconciled with their traditional methodological practices.

Spatial information theorists and geographic information scientists have not normally drawn from humanities research cases for their development of theoretical models or the specific software and systems built upon such models. It is our belief the time is ripe for fruitful dialog between these groups.

To further and encourage such dialog, we invite papers that explicitly address one or more of these distinctive issues, particularly in the context of active or recent humanities research:

• computing over sparse and uncertain data, e.g., the life courses of historical individuals
• comparing and conflating conflicting assertions about the same phenomena from multiple sources
• representing and analyzing place as experienced space
• theorizing historical events and processes and their formal representation as spatial-temporal data, in simple, useful indexing and reasoning systems
• building digital historical gazetteers, challenges for which include:
  • automated and machine-assisted discovery of place references in historical texts
  • place and place-name disambiguation
  • representing not only real‑world places but fictional or speculative ones
• formalizing complex spatio-temporal relations (e.g., topological) in texts; modeling entities with evidence of multi-space, multi-time properties
• integrated methods for performing textual analysis with spatial analysis
• scaling of discovery methods for aggregate analyses on very large collections
• place sentiment analysis
• computational narrative analysis as it relates to space and place
• cartographic representations of historical textual information