cb 4.0 – Abstract of GrapHNR 2023, Squirrel Papers 5(4), No. 1, DOI: 10.5281/zenodo.7915197. Dating “dated sites”: Using Correspondence Analysis to handle relative chronologies as graphs. Florian Thiery 1,2 and Allard W. Mees 1 1 Leibniz-Zentrum für Archäologie (LEIZA), Germany 2 NFDI4Objects, Germany 1 Background “Dated sites” in archaeology are usually not “dated sites”. In the frst century AD e.g., there are only two verifable “absolute dated sites”: Pompei (Plinius the Younger, nd, chapter LXV) and Inch- tuthil (Tacitus, nd, chapters XXIX-XXXVII), of which ancient authors indicate their dates. Only parts of the “dated sites” can be set in relative relation to each other, e.g. if they belong to a group of sites within a newly occupied area or if they are part of a string of military sites related to a military campaign etc. For this purpose, we can use e.g. Allen's interval algebra (Allen, 1983; Freksa, 1991), such as “after” or “during” (Cox et al., 2016; Cox and Little, 2022; Shaw, 2022; Thiery, 2013). How- ever, most of the temporality of “dated sites” is usually derived from a series of historical assumptions and interpolations. Yet, the chronology of these materials is often based on material coming from the manifold of other assumed “dated sites”, thus potentially resulting in a circulus vitiosus. On top of that, “dated sites” are frequently given dates like “from - to”, suggesting a dating security which is actually only a probability. A methodological way out of this dilemma is possible when we enhance the assumed external dating evidence and go back to the factual occurrences and overlaps in the data from the suspected “dated sites”, since only these data are free of any temporal interpretations. This results in four diferent research questions: 1. How can any resulting time order of “dated sites” be comprehensively encoded and semanti- cally modelled, e.g. by using Allen’s interval algebra and graph technologies (Cox et al., 2016; Cox and Little, 2022)? 2. How can a reproducible algorithm deal with incomplete or vague dates to fx missing start or endpoints by creating “virtual fuzzy and wobbly dates”? Are graph-based digital tools like Alligator (Thiery and Mees, 2022) or the Academic Meta Tool (AMT) (Unold et al., 2019) usable for this purpose? 3. How can results be visualised for researchers using graphs, timelines or maps (Thiery, 2013, chapter 9)? 4. Do we need a diferent concept of temporalities for such “dated sites”? 1