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With relational perspectives, we examine the potential of traversing cultural collections along the richness of individual facets and relations through the process of developing an exploration-centered visualization. Cultural collections can contain thousands of artifacts, of which each typically possesses a diverse set of properties and individual facets constituting a unique relationship to the rest of the collection. Therefore, to create an appropriate representation of the complex data of each underlying artifact, oftentimes, it is not only interesting to get an overview of the entire collection from one perspective, but to explore the specific context of an artifact and the various relations it may have to other items. To investigate the potential of relational perspectives, we selected an art collection as a particularly promising case study. By following and reporting from a collaborative and iterative design process with an art museum, we developed a web interface that contrasts a collection overview with three situated visualizations each exposing a different kind of relational perspective on the art collection from an artifact.
Today, digital learning resources in architecture are spread over a growing number of repositories world-wide. Students of architecture face increasing problems finding and being aware of appropriate learning resources they need within their collaborative and/or exploratory learning scenarios. The Metadata for Architectural Contents in Europe (MACE) system addresses these issues by intelligently aggregating and linking information about learning resources from various repositories. We show how, by establishing explicit relations between the learning resources and by adding community features, students are supported in their learning activities. First experiments indicate that the chosen approach improves the results students can achieve in their studies.
A lot of information that is already available on the Web, or retrieved from local information sys-tems and social networks, is structured in data silos that are not semantically related. Semantic technologies make it apparent that the use of typed links that directly express their relations are an advantage for every application that can reuse the incorporated knowledge about the data. For this reason, data integration, through reengineering (e.g., triplify) or querying (e.g., D2R), is an important task in order to make information available for everyone. Thus, in order to build a semantic map of the data, we need knowledge about data items itself and the relation between heterogeneous data items. Here we present our work of providing Lexical Linked Data (LLD) through a meta-model that contains all the resources and gives the possibility to retrieve and navigate them from different per-spectives. After giving the definition of Lexical Linked Data, we describe the existing datasets we collected and the new datasets we included. Here we describe their format and show some use cases where we link lexical data, and show how to reuse and inference semantic data de-rived from lexical data. Different lexical resources (MultiWordNet, EuroWordNet, MEMODATA Lexicon, the Hamburg Methaphor Data-base) are connected to each other towards an Integrated Vocabulary for LLD that we evaluate and present.
Affect control processes
(2015)
This paper describes a novel method for building affectively intelligent human-interactive agents. The method is based on a key sociological insight that has been developed and extensively verified over the last twenty years, but has yet to make an impact in artificial intelligence. The insight is that resource bounded humans will, by default, act to maintain affective consistency. Humans have culturally shared fundamental affective sentiments about identities, behaviours, and objects, and they act so that the transient affective sentiments created during interactions confirm the fundamental sentiments. Humans seek and create situations that confirm or are consistent with, and avoid and suppress situations that disconfirm or are inconsistent with, their culturally shared affective sentiments. This “affect control principle” has been shown to be a powerful predictor of human behaviour. In this paper, we present a probabilistic and decision-theoretic generalisation of this principle, and we demonstrate how it can be leveraged to build affectively intelligent artificial agents. The new model, called BayesAct, can maintain multiple hypotheses about sentiments simultaneously as a probability distribution, and can make use of an explicit utility function to make value-directed action choices. This allows the model to generate affectively intelligent interactions with people by learning about their identity, predicting their behaviours using the affect control principle, and taking actions that are simultaneously goal-directed and affect-sensitive. We demonstrate this generalisation with a set of simulations. We then show how our model can be used as an emotional “plug-in” for artificially intelligent systems that interact with humans in two different settings: an exam practice assistant (tutor) and an assistive device for persons with a cognitive disability.
The Marker Cluster
(2016)
The growing amount of gathered, stored and available data is creating a need for useful mass-data visualizations in many domains. The mapping of large spatial data sets is not only of interest for experts anymore, but, with regard to the latest advances in web cartography, also moves into the domain of public cartographic applications. One interactive web-based cartographic interface design pattern that helps with visualizing and interacting with large, high density data sets is the marker cluster; a functionality already in use in many web-based products and solutions. In this article, the author will present their ongoing research on the problem of “too many markers.” They will present an empirical evaluation and comparison of marker cluster techniques and similar approaches, including heatmaps and tiled heatmaps. They conclude with a first concept for overcoming some of the obstacles that they were able to identify in their study and thereby introduce a new direction for further research.
Many datasets have multiple perspectives – for example space, time and description – and often analysts are required to study these multiple perspectives concurrently. This concurrent analysis becomes difficult when data are grouped and split into small multiples for comparison. A design challenge is thus to provide representations that enable multiple perspectives, split into small multiples, to be viewed simultaneously in ways that neither clutter nor overload. We present a design framework that allows us to do this. We claim that multi-perspective comparison across small multiples may be possible by superimposing perspectives on one another rather than juxtaposing those perspectives side-by-side. This approach defies conventional wisdom and likely results in visual and informational clutter. For this reason we propose designs at three levels of abstraction for each perspective. By flexibly varying the abstraction level, certain perspectives can be brought into, or out of, focus. We evaluate our framework through laboratory-style user tests. We find that superimposing, rather than juxtaposing, perspective views has little effect on performance of a low-level comparison task. We reflect on the user study and its design to further identify analysis situations for which our framework may be desirable. Although the user study findings were insufficiently discriminating, we believe our framework opens up a new design space for multi-perspective visual analysis.
Experiments using Semantic Web technologies to connect IUGONET, ESPAS and GFZ ISDC data portals
(2016)
E-science on the Web plays an important role and offers the most advanced technology for the integration of data systems. It also makes available data for the research of more and more complex aspects of the system earth and beyond. The great number of e-science projects founded by the European Union (EU), university-driven Japanese efforts in the field of data services and institutional anchored developments for the enhancement of a sustainable data management in Germany are proof of the relevance and acceptance of e-science or cyberspace-based applications as a significant tool for successful scientific work. The collaboration activities related to near-earth space science data systems and first results in the field of information science between the EU-funded project ESPAS, the Japanese IUGONET project and the GFZ ISDC-based research and development activities are the focus of this paper. The main objective of the collaboration is the use of a Semantic Web approach for the mashup of the project related and so far inoperable data systems. Both the development and use of mapped and/or merged geo and space science controlled vocabularies and the connection of entities in ontology-based domain data model are addressed. The developed controlled vocabularies for the description of geo and space science data and related context information as well as the domain ontologies itself with their domain and cross-domain relationships will be published in Linked Open Data.
As cultural institutions are digitizing their artifacts and interlinking their collections, new opportunities emerge to engage with cultural heritage. However, it is the often comprehensive and complex nature of collections that can make it difficult to grasp their distribution and extent across a variety of dimensions. After a brief introduction to the research area of collection visualizations, this paper presents a design study visualizing an aggregated collection from diverse cultural institutions in Germany. We detail our iterative design process leading to prototypical implementations of four stylistically and functionally coordinated visualizations, each one focusing on different facets of the collection.
Photography in the digital
(2018)
Photography in the digitally created or digitized reality is an everyday activity that is rarely discussed in the context of photographic debates. This refers to practices such as in-game photography or, simpler yet, the screenshot. The paper focuses on their history, the specific status and materiality of these images of screens. Their (hi)story begins with screen image photography of measured data on cathode ray tubes and the photographic capture of x-ray screens. Screenshots and in-game photography can be seen throughout this context but they are cameraless and can therefore be understood and discussed within a long history of experimental photographic practices. Should we speak here at all of photography? If so, what is their photographic specificity? Which image of reality do they provide us?