Usability-Ergebnisse als Wissensressource in Organisationen

Durch den Prozess der nutzerzentrierten Softwareentwicklung sammeln Organisationen wichtige Erkenntnisse über die Nutzer ihre Produkte, deren Arbeitsaufgaben und über die Nutzungskontexte, in dem diese sie anwenden. Diese Arbeit untersucht, wie derartige Usability-Ergebnisse in einer Organisation langfristig als Durch den Prozess der nutzerzentrierten Softwareentwicklung sammeln Organisationen wichtige Erkenntnisse über die Nutzer ihrer Produkte, deren Arbeitsaufgaben und über die Nutzungskontexte, in denen sie angewendet werden. Diese Arbeit untersucht, wie derartige Usability-Ergebnisse in einer Organisation langfristig als Wissensressource eingesetzt werden können, um die Usability zukünftiger Produkte zu verbessern und die Effizienz des nutzerzentrierten Entwicklungsprozesses zu optimieren. Im Fokus stehen dabei interne Usability-Beauftragte als Anwender dieser Wissensressource: Da diese innerhalb ihrer Organisation für die dort entwickelten Produkte verantwortlich sind, haben sie ein besonders hohes Interesse an der nachhaltigen Nutzung der erhobenen Usability-Ergebnisse. Zu einer organisationsinternen Nutzung von Usability-Ergebnissen existieren bereits Ansätze aus der Forschung zu nutzerzentrierten Entwicklungsprozessen im Bereich der Mensch-Computer-Interaktion, die unterschiedliche Ziele verfolgen. (Hughes, 2006; Douglas, 2007; Vilbergsdottir et al., 2014). Einen frühen Ansatz stellt Andre et al. (2001) mit dem User Action Framework vor, dessen Anwendung jedoch aufwendig sein kann (Hornbæk et al., 2008). Vorschläge für die Klassifizierung von empirischen Usability-Ergebnissen werden bislang vor allem im Kontext der Forschung zu Usability-Methoden eingesetzt (etwa Lavery et al., 1997; Hornbæk et al., 2008). In anderen Bereichen finden sie jedoch keine breite Anwendung, da sie nicht auf die Anwendungsfälle für Usability-Information in Organisationen abgestimmt sind. Als eine zentrale Fragestellung dieser Arbeit wird daher untersucht, für welche Anwendungsfälle eine Sammlung von Usability-Ergebnissen eingesetzt werden kann (Forschungsfrage RQ1). Dafür werden qualitativ ausgerichtete Interviews (n=8) mit internen Usability-Beauftragten sowie Fokusgruppen in zwei Organisationen durchgeführt. Im Rahmen dieser Studien können außerdem die Anforderungen an die Wissensorganisation und an die Informationsinteraktion für die Nutzung von Usability-Ergebnissen als Wissensressource analysiert werden (RQ2). Die Anforderungen werden als ein prototypisches Usability-Informationssystem umgesetzt, welches den Zugang zu einer Sammlung von Usability-Ergebnissen bereitstellt. In einer Studie mit Usability-Beauftragten (n=11) wird dieses System evaluiert, um Rückschlüsse auf die zugrunde liegenden Anforderungen zu ermöglichen. Im Rahmen der Studie werden zudem die Entscheidungsprozesse diskutiert, die angewendet werden, wenn Usability-Ergebnisse auf andere Kontexte übertragen oder verallgemeinert werden sollen (RQ3). Weiterhin werden die Faktoren und Barrieren untersucht, welche die Akzeptanz von Usability-Ergebnissen als Wissensressource in einer Organisation beeinflussen (RQ4). Die Untersuchungen zeigen, dass Usability-Ergebnisse bereits in vielen Organisationen gesammelt und gezielt eingesetzt werden. Die erhobenen Anwendungsfälle (RQ1) umfassen die Übertragung von vorhandenen Ergebnissen auf aktuelle Gestaltungsentscheidungen, Lernprozesse, analytische Fragestellungen und die Verallgemeinerung zu internen Richtlinien. Zu den identifizierten Anforderungen für die Organisation von Usability-Wissen (RQ2) gehört die Kombination von produktübergreifenden und produktbezogenen Metadaten. Die empirischen Evaluierungsergebnisse aus Nutzertests sollten mit den zugrunde liegenden Daten, vor allem aber mit den resultierenden Lösungsvorschlägen verknüpft werden. Bei der Gestaltung der Informationsinteraktion sollten die gezielte Suche, der Umgang mit potenziell unbekannter oder wechselnder Terminologie, aber auch explorative Such- und Lernprozesse unterstützen werden. Wenn Usability-Ergebnisse in einer Organisation mit dem Ziel der Vollständigkeit erhoben werden, können darauf auch Funktionen für die quantitative Analyse und für die Prozessbewertung aufbauen. Für die Bewertung der Übertragbarkeit von Usability-Ergebnissen (RQ3) sind eine Reihe von Entscheidungskriterien und Hinweisen relevant, anhand derer ihre Zuverlässigkeit überprüft und der Erhebungskontext hinsichtlich der Relevanz für eine aktuelle Fragestellung bewertet werden kann. Die Akzeptanz der Anwendung von Usability-Wissen (RQ4) erscheint primär von dem Aufwand abhängig, der für die Erschließung der Ergebnisse erforderlich ist. Die meisten der Teilnehmer bewerten den Aufwand im Verhältnis zu den erwarteten Vorteilen jedoch als angemessen. Mögliche Barrieren für die Wissensteilung können aus der Befürchtung entstehen, die Kontrolle über die Interpretation der Ergebnisse zu verlieren, sowie aus der Wahrnehmung als öffentliche Kritik an den jeweiligen Produktverantwortlichen. Die Ergebnisse dieser Arbeit können dabei helfen, die Unterstützung für die Nutzung von Usability-Ergebnissen als Wissensressource auf die erhobenen Anwendungsfälle auszurichten. Dafür werden Empfehlungen zu möglichen Ausrichtungen eines Usability-Informationssystems in Organisationen gegeben. Die Ergebnisse verweisen außerdem auf das große Potenzial für weitere Forschungsvorhaben in diesem Bereich, sowohl in Hinblick auf eine bessere Unterstützung des Wissensmanagements von Usability-Ergebnissen als auch in Bezug auf die Übertragung der grundlegenden Erkenntnisse dieser Arbeit auf andere Anwendungsdomänen, etwa im Bereich des Managements von Forschungsdaten.User centered software development provides organizations with valuable insights about the users of their software, about their work tasks and the various contexts in which a product is used. This dissertation explores how organizations can profit even more from such results in the long term by using them as an internal knowledge resource for improving the usability of future products and for increasing the efficiency of user centered processes. This topic will be investigated for in-house usability consultants as the primary target group of such a resource. In-house consultants are responsible for the quality of the products developed in their company, and the sustainable management of internal usability results therefore is of particular interest to them. In the research field of human computer interaction and user centered design, several approaches have already been proposed which can be used to systematize usability results in order to pursue a variety of goals (e.g. Hughes 2006; Douglas 2007; Vilbergsdottir et al. 2014). The User Action Framework (Andre et al. 2001) is an important contribution in this area. Its implementation, however, may prove to be difficult for many organizations because applying it was found to be resource intensive (Hornbæk et al., 2008). Other classification systems for usability problems have predominantly been in use in scientific studies on the evaluation of usability methods (e. g. Lavery et al. 1997; Hornbæk & Frøkjær 2008). These approaches have not been widely adopted because of the efforts involved in applying them, and because they do not take into account relevant use cases for usability information in organizations. The identification of use cases for the internal application of usability results therefore constitutes an important research question of this dissertation (research question RQ1). Qualitative interviews with in-house usability consultants (n=8) as well as focus groups in two organizations are conducted in order to investigate this question and to elicit usage requirements of an usability information system (research question RQ2). A prototypical usability information system implements these requirements based on a set of realistic usability results. The system and the proposed requirements are evaluated in an additional study with usability consultants (n=11). In the context of this study, criteria for reusing and generalizing usability results can be examined from the point of view of the participants (research question RQ3). In addition, the factors and barriers influencing the process of sharing and using usability knowledge have been investigated (research question RQ4). Results demonstrate that usability results have already been collected and applied to different use cases in many organizations (RQ1), including their direct application to current design decisions, learning and exploration, analytic questions, and the creation of internal usability standards. The organization of usability results (RQ2) requires a combination of product-specific characteristics with more general attributes as metadata for search and analysis. Results from user studies should be linked to the underlying empirical data and to the resulting design recommendations. Requirements for information interaction include support for the targeted search for usability results, dealing with potentially unknown or changing terminology, as well as possibilities for exploratory search and learning. If results are collected comprehensively in an organization, features for information analysis can be used to support the improvement of development processes. A number of different criteria are used to assess the reliability of usability results and the fit between the context in which a result was elicited and the context to which the result is to be applied. These aspects together provide the basis for deciding about the transferability of results (RQ3). Acceptance of the application of usability results as an information resource (RQ4) primarily depends on the amount of effort which is required for documenting these results. However, most participants expect the benefits to outweigh these efforts. Possible barriers for sharing usability results also include concerns about the loss of control over their interpretation as well as the perception of published results as criticism by those who are responsible for a product. In addition to describing existing practices, the results of this dissertation are intended to offer assistance for the application of usability results as an information resource in different use cases. Accordingly, recommendations about different categories of usability information systems are presented. The findings indicate further possibilities for research with the goal of improving knowledge management for usability results and may also be applied to other domains such as research data management

Korpuslinguistik

The study examines the concept of patterned language usage in scientific texts and, based on a data-led corpus analysis, describes scientific style at a formal and pragmatic level. With theoretical grounding in multiple linguistic sub-disciplines, the book makes a major contribution to text-type research, the discussion of standards, and to the study of writing

Exploratory search in time-oriented primary data

In a variety of research fields, primary data that describes scientific phenomena in an original condition is obtained. Time-oriented primary data, in particular, is an indispensable data type, derived from complex measurements depending on time. Today, time-oriented primary data is collected at rates that exceed the domain experts’ abilities to seek valuable information undiscovered in the data. It is widely accepted that the magnitudes of uninvestigated data will disclose tremendous knowledge in data-driven research, provided that domain experts are able to gain insight into the data. Domain experts involved in data-driven research urgently require analytical capabilities. In scientific practice, predominant activities are the generation and validation of hypotheses. In analytical terms, these activities are often expressed in confirmatory and exploratory data analysis. Ideally, analytical support would combine the strengths of both types of activities. Exploratory search (ES) is a concept that seamlessly includes information-seeking behaviors ranging from search to exploration. ES supports domain experts in both gaining an understanding of huge and potentially unknown data collections and the drill-down to relevant subsets, e.g., to validate hypotheses. As such, ES combines predominant tasks of domain experts applied to data-driven research. For the design of useful and usable ES systems (ESS), data scientists have to incorporate different sources of knowledge and technology. Of particular importance is the state-of-the-art in interactive data visualization and data analysis. Research in these factors is at heart of Information Visualization (IV) and Visual Analytics (VA). Approaches in IV and VA provide meaningful visualization and interaction designs, allowing domain experts to perform the information-seeking process in an effective and efficient way. Today, bestpractice ESS almost exclusively exist for textual data content, e.g., put into practice in digital libraries to facilitate the reuse of digital documents. For time-oriented primary data, ES mainly remains at a theoretical state. Motivation and Problem Statement. This thesis is motivated by two main assumptions. First, we expect that ES will have a tremendous impact on data-driven research for many research fields. In this thesis, we focus on time-oriented primary data, as a complex and important data type for data-driven research. Second, we assume that research conducted to IV and VA will particularly facilitate ES. For time-oriented primary data, however, novel concepts and techniques are required that enhance the design and the application of ESS. In particular, we observe a lack of methodological research in ESS for time-oriented primary data. In addition, the size, the complexity, and the quality of time-oriented primary data hampers the content-based access, as well as the design of visual interfaces for gaining an overview of the data content. Furthermore, the question arises how ESS can incorporate techniques for seeking relations between data content and metadata to foster data-driven research. Overarching challenges for data scientists are to create usable and useful designs, urgently requiring the involvement of the targeted user group and support techniques for choosing meaningful algorithmic models and model parameters. Throughout this thesis, we will resolve these challenges from conceptual, technical, and systemic perspectives. In turn, domain experts can benefit from novel ESS as a powerful analytical support to conduct data-driven research. Concepts for Exploratory Search Systems (Chapter 3). We postulate concepts for the ES in time-oriented primary data. Based on a survey of analysis tasks supported in IV and VA research, we present a comprehensive selection of tasks and techniques relevant for search and exploration activities. The assembly guides data scientists in the choice of meaningful techniques presented in IV and VA. Furthermore, we present a reference workflow for the design and the application of ESS for time-oriented primary data. The workflow divides the data processing and transformation process into four steps, and thus divides the complexity of the design space into manageable parts. In addition, the reference workflow describes how users can be involved in the design. The reference workflow is the framework for the technical contributions of this thesis. Visual-Interactive Preprocessing of Time-Oriented Primary Data (Chapter 4). We present a visual-interactive system that enables users to construct workflows for preprocessing time-oriented primary data. In this way, we introduce a means of providing content-based access. Based on a rich set of preprocessing routines, users can create individual solutions for data cleansing, normalization, segmentation, and other preprocessing tasks. In addition, the system supports the definition of time series descriptors and time series distance measures. Guidance concepts support users in assessing the workflow generalizability, which is important for large data sets. The execution of the workflows transforms time-oriented primary data into feature vectors, which can subsequently be used for downstream search and exploration techniques. We demonstrate the applicability of the system in usage scenarios and case studies. Content-Based Overviews (Chapter 5). We introduce novel guidelines and techniques for the design of contentbased overviews. The three key factors are the creation of meaningful data aggregates, the visual mapping of these aggregates into the visual space, and the view transformation providing layouts of these aggregates in the display space. For each of these steps, we characterize important visualization and interaction design parameters allowing the involvement of users. We introduce guidelines supporting data scientists in choosing meaningful solutions. In addition, we present novel visual-interactive quality assessment techniques enhancing the choice of algorithmic model and model parameters. Finally, we present visual interfaces enabling users to formulate visual queries of the time-oriented data content. In this way, we provide means of combining content-based exploration with content-based search. Relation Seeking Between Data Content and Metadata (Chapter 6). We present novel visual interfaces enabling domain experts to seek relations between data content and metadata. These interfaces can be integrated into ESS to bridge analytical gaps between the data content and attached metadata. In three different approaches, we focus on different types of relations and define algorithmic support to guide users towards most interesting relations. Furthermore, each of the three approaches comprises individual visualization and interaction designs, enabling users to explore both the data and the relations in an efficient and effective way. We demonstrate the applicability of our interfaces with usage scenarios, each conducted together with domain experts. The results confirm that our techniques are beneficial for seeking relations between data content and metadata, particularly for data-centered research. Case Studies - Exploratory Search Systems (Chapter 7). In two case studies, we put our concepts and techniques into practice. We present two ESS constructed in design studies with real users, and real ES tasks, and real timeoriented primary data collections. The web-based VisInfo ESS is a digital library system facilitating the visual access to time-oriented primary data content. A content-based overview enables users to explore large collections of time series measurements and serves as a baseline for content-based queries by example. In addition, VisInfo provides a visual interface for querying time oriented data content by sketch. A result visualization combines different views of the data content and metadata with faceted search functionality. The MotionExplorer ESS supports domain experts in human motion analysis. Two content-based overviews enhance the exploration of large collections of human motion capture data from two perspectives. MotionExplorer provides a search interface, allowing domain experts to query human motion sequences by example. Retrieval results are depicted in a visual-interactive view enabling the exploration of variations of human motions. Field study evaluations performed for both ESS confirm the applicability of the systems in the environment of the involved user groups. The systems yield a significant improvement of both the effectiveness and the efficiency in the day-to-day work of the domain experts. As such, both ESS demonstrate how large collections of time-oriented primary data can be reused to enhance data-centered research. In essence, our contributions cover the entire time series analysis process starting from accessing raw time-oriented primary data, processing and transforming time series data, to visual-interactive analysis of time series. We present visual search interfaces providing content-based access to time-oriented primary data. In a series of novel explorationsupport techniques, we facilitate both gaining an overview of large and complex time-oriented primary data collections and seeking relations between data content and metadata. Throughout this thesis, we introduce VA as a means of designing effective and efficient visual-interactive systems. Our VA techniques empower data scientists to choose appropriate models and model parameters, as well as to involve users in the design. With both principles, we support the design of usable and useful interfaces which can be included into ESS. In this way, our contributions bridge the gap between search systems requiring exploration support and exploratory data analysis systems requiring visual querying capability. In the ESS presented in two case studies, we prove that our techniques and systems support data-driven research in an efficient and effective way

Digital History

Research and teaching in history have undergone profound changes within the scope of digitalization. This volume asks questions such as: What changes is digitalization making possible in the way that historical research is carried out and communicated today? What new objects, methods, and tools are available to researchers today and what research findings do they produce

Explorative Suche in zeitbasierten Primärdaten

Die Ära des Big Data birgt gewaltige Potenziale für die datenzentrierte Forschung, denen Herausforderungen wie die Größe, die Qualität oder temporale Aspekte der Daten gegenüberstehen. Für die explorative Suche nach unerforschtem Wissen in komplexen Daten benötigen Domänenexperten effektive Analysetechniken und -systeme. Im Design dieser Systeme lassen sich die Kompetenzen von Data Scientists mit denen der Domänenexperten vereinen. Am Beispiel von zeitbasierten Primärdaten präsentiere ich in meiner Dissertation Konzepte, Richtlinien, Techniken und Systeme für die explorative Suche zur Unterstützung der datenzentrierten Forschung. Dabei verfolge ich in einem Visual-Analytics-Ansatz die strikte Kopplung von visuell-interaktiven Benutzerschnittstellen mit algorithmischen Modellen zur Datenanalyse. Beim Design von explorativen Suchsystemen ermögliche ich den Vergleich und die Auswahl von Modellen, unter Einbezug von Domänenexperten