Kurt Englmeier

Interactive Visual User Interfaces: A Survey

Following a short survey of input data types onwhich to construct interactive visual userinterfaces, we report on a new and recentimplementation taking concept hierarchies asinput data. The visual user interfacesexpress domain ontologies which are based onthese concept hierarchies. We detail aweb-based implementation, and show examples ofusage. An appendix surveys related systems,many of them commercial.

Tag clouds for displaying semantics: the case of filmscripts

We relate tag clouds to other forms of visualization, including planar or reduced dimensionality mapping, and to Kohonen self-organizing maps. Using a modified tag cloud visualization, we incorporate other information into it, including text sequence and most pertinent words. Our notion of word pertinence goes beyond just word frequency and instead takes a word in a mathematical sense as located at the average of all of its pairwise relationships. We capture semantics through context, taken as all pairwise relationships. Our domain of application is that of filmscript analysis. The analysis of filmscripts, always important for cinema, is experiencing a major gain in importance in the context of television. Our objective in this paper is to visualize the semantics of filmscript, and beyond filmscript any other partially structured, time-ordered sequence of text segments. In particular, we develop an innovative approach to plot characterization.

Choreography of web services based on natural language storybooks

Universally available services, which communicate in a standardized way, can provide a new generation of middleware. Harnessing the advantages of this promising middleware technology, however, means to be capable to understand and to handle its design language which emerges from standards like SOAP, WSDL, BPEL, etc. These languages are necessary for finding, composing and orchestrating web services. If at all, only IT experts are familiar with these languages.The key actors, the domain experts of business processes, however, are not IT experts, and thus do not become the main designers. WS-Talk is a research project that encourages the co-existence of Natural Language and Web service technology. It reinforces the role of domain experts in designing business processes without having to resort to their IT colleagues. In our approach business process experts write storybooks in their own language. Their instructions are matched with semantics that represent application logic that, in turn, supports the automatic composition of software components. The WS-Talk products currently support organizations in managing their own and individual information, i.e. to set up their own enterprise search engine.

Natural Language Expansion of Web Service Interoperability

This paper presents the Web Service (WS)-Talk interface Layer, a structured natural language interface for the inter-service communication that extends service virtualization to strengthen consumer self-service. While providers will concentrate more on the technical levels of activation and communication within a service network, the users, i.e. the service consumers, will form ad-hoc collaborations between services at the semantic level that suit their own specific needs. We present the Web Service (WS)-Talk layer as a structured-language interface for Web services. This “open building block” can be implemented by both the service designers who as providers are more concerned with the architecture of the underlying service model and the service consumers who as users will seek to specify Web services as solutions to specific problems. Through a semantic layer, WS-Talk creates an abstraction layer that enables views on services expressed in natural language.

The Semantic Facet of Ubiquitous Computing

Ubiquitous computing has an impact on future information provision as it rises context-awareness significantly. Information systems are thus more in the position to view the users within their actual ambience and provide information suitable for information needs that are intertwined with the situation they are actually experiencing. Context-aware information provision locates, for instance, a visitor within a museum or exhibition and delivers automatically information on objects exposed close to the visitors location. Context can also be more abstract if it addresses a situation that is part of a conversation, a newspaper article, or TV news. This paper describes an interface layer for abstract facets in context-awareness that allow interoperability among complex and volatile populations of different data sources. They map these heterogeneous content sources into a unified information space. The marriage of semantic web technologies with text mining catches up with the critical element of automating the collection of content-relevant information and of the construction of a coherent context.

The Benefit of Thinking Small in Big Data

No doubt, big data technology can be a key enabler for data-driven decision making. However, there are caveats. Processing technology for unstructured and structured data alone–with or without Artificial Intelligence–will not suffice to catch up the promises made by big data pundits. This article argues that we should be level-headed about what we can achieve with big data. We can achieve a lot of these promises if we also achieve to get our interests and requirements better reflected in design or adaptation of big data technology. Economy of scale urges provider of big data technology to address mainstream requirements, that is, analytic requirements of a broad clientele. Our analytical problems, however, are rather individual, albeit mainstream only to a certain extent. We will see many technology add-ons for specific requirements, with more emphasis on human interaction too, that will be essential for the success in big data. In this article, we take machine translation as an example and a prototypical translation memory as add-on technology that supports users to turn the faulty automatic translation into a useful one.

Data Scientist - Manager of the Discovery Lifecycle

Data Scientists are the masters of Big Data. Analyzing masses of versatile data leads to insights that, in turn, may connect to successful business strategies, crime prevention, or better health care just to name a few. Big Data is primarily approached as mathematical and technical challenge. This may lead to technology design that enables useful insights from Big Data. However, this technology-driven approach does not meet completely and consistently enough the variety of information consumer requirements. To catch up with the versatility of user needs, the technology aspect should probably be secondary. If we adopt a user-driven approach, we are more in the position to cope with the individual expectations and exigencies of information consumers. This article takes information discovery as the overarching paradigm in data science and explains how this perspective change may impact the view on the profession of the data scientist and, resulting from that, the curriculum for the education in data science. It reflects the result from discussions with companies participating in our student project cooperation program. These results are groundwork for the development of a curriculum framework for Applied Data Science.

Interaction for Information Discovery Empowering Information Consumers

Information Discovery (ID) is predominantly addressed by approaches from Artificial Intelligence (AI). Automatic ID scans large amounts of data and identifies as many potential candidates for discovery as possible. Mass discovery may in fact serve the needs of many information consumers. However, that does not mean that it addresses a broad range of user interests, too. Economies of scale urge the development of automatic tools to address user needs only from a certain critical mass. Hence, many user needs remain unaddressed. This is where HCI comes into play and provides fundamentals for pattern languages that empower information consumers to stage their own information discovery. With this paper we want to draw attention to an approach that is developed around the paradigm of human-centered interaction design. We present an Open Discovery Language that can completely be controlled by information consumers.

A Context Description Language for Medical Information Systems

Contextualized delivery of information is one of the many strengths of ubiquitous computing. It makes information actionable and helps us to better understand our situations. In the realm of healthcare, contextual information provides a terse but precise picture of the patient’s health situation. The patient context can have many facets, ranging from nutrition context over health heritage context to the context of symptoms, just to name a few. Setting up the correct health condition context of a patient favors better and faster recognition of the patient’s actual health situation.

The role of natural language in social information engineering

In this paper we present work-in-progress - a technology platform for Social Collaboration in the context of Personalized Information Extraction. In particular, we consider elements of user-centered software engineering as it converges on the development of folksonomies. Results from our work-in-progress demonstrate to what extent non-IT users can apply natural language when managing their IT-based processes addressing information integration. We concentrate on the language model that supports the development of process-related folksonomies in the context of retrieving and merging textual information from different sources concerning legal documents. Findings in our work-in-progress underpin the conjecture that the computational nature of natural language overcomes the inherent problem of ambiguity when applied in a collaboration context that the users are aware of.