This paper will present an experimental approach to representing historical data in digital format, in particular in situations where there are multiple and contested readings of that information, via use of a five-point ‘pentile’ data model based on historical assertions.
One of the difficulties inherent in representations of historical data, especially in prosopographical or event modelling contexts, has been the lack of capacity to effectively capture historical argumentation. This tends to result in approaches that try to reduce to a minimum the presentation of historical argumentation within the dataset, without disambiguation and clarification of the linked sections of primary source material. The “factoid model” commonly used for prosopographical databases is a key example of this type, with its explicit assumption that historians will, if they wish, provide further layers of analysis themselves. 
However, reduced models of this sort have proven dissatisfying for historians. For one thing, it is already widely accepted that there is no such thing as a “neutral” dataset: the inherent needs of categorisation require historical judgement which may be open to discussion and challenge, especially in fraught areas like the meanings of historical identities.  The models used often have limited capacity for showcasing and presenting the argumentation and historical thought involved in these necessary decisions, which at times weakens their utility for subsequent users.
Furthermore, a dataset of the kind discussed above has limitations on its use cases. If conflicting source data is not disambiguated, it cannot effectively be mapped, or looked at through comparative visualisations: the results of doing so would be nonsensical, as there would be nothing to stop individuals being in multiple places at once, or both dead and alive simultaneously, where sources conflict on those points. It would take a bold scholar to try and argue, for example, that the Georgian Kartlis Tskhovreba’s hazy chronology of the late 12th century Byzantine collapse is as good a representation of events as the chronicle of Niketas Choniates, who was an eyewitness to many relevant events. But in an event model using the minimum-argument rule, this would be the implied logic at the data level and thus in any analyses of that data. All this should not be taken to mean that there are no use cases for minimum-argument models: far from it, as these systems have the strong advantages of being comparatively quick to compile and providing good close text linkages, making them useful for indexing functions. There is nonetheless a clear gap in their effective usage, which historians have struggled to adequately fill through adaptations and workarounds within this model.
We have therefore adopted an alternative approach to the problem. This involves an expansion of the LOD “triple” data approach, in which data is stored with three points, a subject, predicate, and object. We expand this to a five point system: subject, predicate, object, asserter, and source. This turns a specific triple into a referenced assertion, with an explicit distinction between the primary source of information and the modern interpreter of that information. The proposed system thereby provides a simple data structure that attempts to capture historical argumentation, with its inherent sets of disagreements and conflicts, rather than either representing a single abstracted proposition of historical fact or representing a textual reading that makes no attempt to differentiate the respective merits of source propositions. With this “pentile” expansion of the triple structure, we are no longer constrained by a minimal-argumentation approach to reading the texts. If we are building a model of what historians consider to have happened, we can represent the majority of this argumentation in this flexible but simple data format.
It should be noted that the source reference in the pentile need not be in relation to a singular element of a primary source, as for a factoid – for example, the natural reference point for archaeological data might be a report or paper. Indeed there is no reason why secondary argumentation should not provide the “source” element, especially when particularly close argumentation or discussion of lacunae are necessary to provide the full basis for an assertion. Our system may thus particularly be seen as a historical argumentation model rather than a model or index of source data, providing an engagement point for historians of a particular area that dovetails more closely with the mixtures of primary evidence and secondary argument familiar in most historical reasoning.
As to the potential scope of information that the model can cover, our pilot project suggests that it is well suited to modelling narratives or prosopographical data, but can also be used with a range of other reference points. The presence of discrete and discernible entities is one of the largest requirements, though that does not necessarily mean consistent identification – if a named “Alexios” might be Alexios I or his grandson who died in 1142, for example, then this could be modelled as a third Alexios with “IsSameAs” or a similar predicate connecting him to both the aforementioned prosopons (also connected, naturally, to the scholar who is making this identification.) However, less consistently defined entities, and arguments over entity definitions (e.g. what constitutes “paganism” or “heterodoxy”) may be harder to capture with this system, an area that could be interesting for ongoing research.
By formalising these elements of historical argumentation, we ultimately hope to provide a new basis for their examination and comparison, tightening arguments into systems where the precise conflicts of conclusion between different historians can be made visible at a granular level. The system may additionally act as a potential tool for scholars who wish to present large scale historical datasets in a consistent and interchangeable format, and with appropriate predicates will allow for compatible exports in accordance with ontologies such as CIDOC-CRM and Symogih.   It may further allow discussions of current historical analyses of particular periods to be better differentiated from presentations of underlying sources, and the presentation of these in ways that preserve the fundamentals of historical argumentation and allow further debate to take place most fruitfully.
 Bradley, John, Pasin, Michele, 2015.”Factoid-based prosopography and computer ontologies: towards an integrated approach”, Digital Scholarship in the Humanities, 30 (1).
 Drucker, Johanna. 2011. “Humanities Approaches to Graphical Display.” Digital Humanities Quarterly 5 (1). http://www.digitalhumanities.org/dhq/vol/5/1/000091/000091.html; Posner, Miriam. 2016. “What’s Next: The Radical, Unrealized Potential of Digital Humanities.” In Debates in the Digital Humanities 2016, edited by Matthew K. Gold and Lauren F. Klein. Minneapolis: University of Minnesota Press. https://dhdebates.gc.cuny.edu/read/untitled/section/a22aca14-0eb0-4cc6-a622-6fee9428a357.
 Le Boeuf, Patrick, Doerr, Martin, Ore, Christian, Stead. Stephen (eds.), 2019. Definition of the CIDOC Conceptual Reference Model version 6.2.7. http://www.cidoc-crm.org/Version/version-6.2.7
 Beretta, Francesco. 2017. L’interopérabilité des données historiques et la question du modèle : l’ontologie du projet SyMoGIH. Presses universitaires de Paris Nanterre. https://halshs.archives-ouvertes.fr/halshs-01559816.
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digitalhistory (2021, 22. Februar). James Baillie/Tara Andrews/Maxim Romanov/Daniel Knox/Maria Vargha: Modelling Historical Information with Structured Assertion Records. Digital History Berlin. Abgerufen am 4. März 2024, von https://doi.org/10.58079/nl29