Mixed Reality games offer new ways to experience cultural heritage spaces, yet their contemporary aesthetics can conflict with the spirit of place of ancient sites. These tensions often limit their deployment in places that might most benefit from the creative reimagining and engagement they afford. Working with the National Trust, we have designed and deployed a mixed reality smartphone game at the Avebury World Heritage Site in Wiltshire, UK; a Neolithic landscape that contains the world's largest prehistoric stone circle. Drawing on an approach we call Polyholomorphism (many whole forms), we bring the player and their device into the experience as creative agents, transforming through different eras of time during the journey. This design invites reflection on technology's changing relationship with place, fostering a sense of belonging to a continuing history. In doing so, it demonstrates how creative design can bridge temporal divides and contribute to more empathetic and transformative encounters with cultural heritage.

The problems of Data Integration/Exchange (DE) and Ontology Based Data Access (OBDA) have been extensively studied across different communities. The underlying problem is common: using a number of differently structured data-sources mapped to a mediating schema/ontology/knowledge-graph, answer a query posed on the latter. In DE, forward-chaining algorithms, collectively known as the chase, transform source data to a new materialised instance that satisfies the ontology and can be directly queried. In OBDA, backward-chaining algorithms rewrite the query over the source schema, taking the ontology into account, in order to execute the rewriting directly on the sources. These two reasoning approaches have seen an individual rise in algorithms, practical implementations, and benchmarks. However, there has not been a principled methodology to compare solutions across both areas. In this paper we provide an original methodology and a benchmark infrastructure - a set of test scenarios, generator and translator tools, and an experimental infrastructure - to allow the translation and execution of a DE/OBDA scenario across areas and among different chase and query-rewriting systems. In the process, we also present a syntactic restriction of linear Tuple Generating Dependencies that precisely captures DL-Lite R , a correspondence previously uninvestigated. We perform cross-approach experiments under a wide range of assumptions, such as the use of different source-to-target mapping languages, shedding light to the interplay between forward-and backward-chaining. Our preliminary results show that, indeed, chase can compete and might overcome query rewriting even in the face of large data especially for complex mapping languages.

With the rising popularity of Virtual Reality (VR), there is also a rising interest in co-located multiplayer experiences, as people want to play VR games together with their friends. As having multiple VR headsets is out of reach to the average consumer, we need to look into different possible ways of including multiple people in this play space. We have created a multi-modal co-located multiplayer VR game, Stuck in Space, that introduces a second player in two ways - one with a PC (the baseline that a lot of current games do), as well as a tracked Phone that can be used as a `window into the virtual world'. We have conducted a user study (n = 24) where we explore the difference in immersion and co-presence between the two versions using two questionnaires (IPQ and NMMoSP), as well as a thematic analysis of the subsequent interview data, from which 5 themes emerged. Surprisingly, we found no significant difference in co-presence or immersion based on the quantitative data. However, the qualitative analysis helps reveal one of the main reasons why that is - maintaining a mental model of the real world while also being in the virtual world makes it harder for the person wearing the headset to immerse themselves and feel co-present. From these themes and sub-themes we theorize that each of the two versions has positives and negatives that cancel each other out in the quantitative data, and for there to be a difference we would need to accentuate or change certain elements of the game. The results show that introducing a second player through a Phone is not detrimental in terms of co-presence and immersion and that it is a viable way of doing so, although certain design considerations would have to be taken into account to minimize the negatives.

Data stories are about communicating data, tailored to a specific audience, with a compelling narrative. Creating them requires a mix of data science and design skills, which can be difficult for beginners. Patterns can help, as they provide tried-and-tested solutions to commonly occurring challenges. 'Narrative patterns' are a particular class of patterns that support data-storytellers in structuring the presentation of data within their story, aiding them in effectively communicating with their audience. Our aim is to understand how such patterns are applied in practice and identify ways they could be of greater use, especially for people new to the field. To this end, we conduct a review of 67 data stories, created by both professional data storytellers and by postgraduate university students studying data-science, to analyse their use of narrative patterns. Starting from a collection of narrative patterns from the literature, we explore which patterns are used more often, either on their own or in combination, and which ones beginners struggle with. From the findings we derive recommendations on how to refine some of the less accessible patterns and for training and tool support, which would allow wider audiences to articulate their data insights effectively.

Summarising data as text helps people make sense of it. It also improves data discovery, as search algorithms can match this text against keyword queries. In this paper, we explore the characteristics of text summaries of data in order to understand how meaningful summaries look like. We present two complementary studies: a data-search diary study with 69 students, which offers insight into the information needs of people searching for data; and a summarisation study, with a lab and a crowdsourcing component with overall 80 data-literate participants, who produced summaries for 25 datasets. In each study we carried out a qualitative analysis to identify key themes and commonly mentioned dataset attributes, which people consider when searching and making sense of data. The results helped us design a template to create more meaningful textual representations of data, alongside guidelines for improving data-search experience overall.

A key area in the research agenda of modelling argumentation is to accurately model argumentation on the social web. In this paper we propose additional extensions to our ontology for argumentation on the social web (which integrates elements of the Argument Interchange Format and the Semantically Interlinked Online Communities project) for the purposes of modelling social and rhetorical tactics used in eristic or irrational arguments. We then present a review of these extensions from a panel of experts in the fields of argumentation modelling, web science, philosophy and open and linked data and discuss the value of modelling social argument, the challenges faced to create usable and accurate models and the completeness, clarity and consistency of our proposed additions.