Wolfgang Jentner

• Doctor of Philosophy
• Research Associate at University of Oklahoma

We present an approach that shows all relevant subspaces of categorical data condensed in a single picture. We model the categorical values of the attributes as co-occurrences with data partitions generated from structured data using pattern mining. We show that these co-occurrences are a-priori allowing us to greatly reduce the search space effect...

The rapid proliferation of social media has created new data stemming from users’ thoughts, feelings, and interests. However, this unprecedented growth has led to the widespread dissemination of misinformation—deliberately or inadvertently false content that can trigger dangerous societal ramifications. Visual analytics combines advanced data analy...

A comprehensive approach to integrated one health surveillance and response Surveillance data plays a crucial role in understanding and responding to emerging infectious diseases; here, we learn why adopting a One Health surveillance approach to EIDs can help to protect human, animal, and environmental health. Over 75% of emerging infectious diseas...

Digital systems for analyzing human communication data have become prevalent in recent years. Intelligence analysis of communications data in investigative journalism, criminal intelligence, and law present particularly interesting cases, as they must take into account the often highly sensitive properties of the underlying operations and data. At...

Linguistic insight in the form of high-level relationships and rules in text builds the basis of our understanding of language. However, the data-driven generation of such structures often lacks labeled resources that can be used as training data for supervised machine learning. The creation of such ground-truth data is a time-consuming process tha...

PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consortium, including the European Society for Paediatric Oncology, two imaging biobanks, and three promin...

The technical progress in the last decades makes photo and video recording devices omnipresent. This change has a significant impact, among others, on police work. It is no longer unusual that a myriad of digital data accumulates after a criminal act, which must be reviewed by criminal investigators to collect evidence or solve the crime. This pape...

We present a modular framework for the rapid-prototyping of linguistic, web-based, visual analytics applications. Our framework gives developers access to a rich set of machine learning and natural language processing steps, through encapsulating them into micro-services and combining them into a computational pipeline. This processing pipeline is...

Explainable Artificial Intelligence describes a process to reveal the logical propagation of operations that transform a given input to a certain output. In this paper, we investigate the design space of explanation processes based on factors gathered from six research areas, namely, Pedagogy, Story-telling, Argumentation, Programming, Trust-Buildi...

Train operators are responsible for maintaining and following the schedule of large-scale railway transport systems. Disruptions to this schedule imply conflicts that occur when two trains are bound to use the same railway segment. It is upon the train operator to decide which train must go first to resolve the conflict. As the railway transport sy...

This chapter surveys visualization techniques for frequent itemsets, association rules, and sequential patterns. The human is crucial in the process of identifying interesting patterns and thus, mining such patterns and visualizing them is important for the decision making. The complementary feedback loop that a user may use to refine parameters th...

Advanced artificial intelligence models are used to solve complex real-world problems across different domains. While bringing along the expertise for their specific domain problems, users from these various application fields often do not readily understand the underlying artificial intelligence models. The resulting opacity implicates a low level...

A fundamental task in criminal intelligence analysis is to analyze the similarity of crime cases, called comparative case analysis (CCA), to identify common crime patterns and to reason about unsolved crimes. Typically, the data are complex and high dimensional and the use of complex analytical processes would be appropriate. State-of-the-art CCA t...

Word clouds are a widely-used technique to visualize documents or collections of documents that arranged in a space-efficient 2D layout. Today’s state of the art in 3D computer graphics and its wide availability pose the question, how a 2D word cloud layout can be transferred into 3D space. In this paper, we discuss a prototypical 3D Wordle-based w...

High-dimensional data poses a significant challenge for analysis, as patterns typically exist only in subsets of dimensions or records. A common approach to reveal patterns, such as meaningful structures or relationships, is to split the data and then to create a visual representation (views) for each data subset. This introduces the problem of ord...

In the research of deliberative democracy, political scientists are interested in analyzing the communication models of discussions, debates, and mediation processes with the goal of extracting reoccurring discourse patterns from the verbatim transcripts of these conversations. To enhance the time-exhaustive manual analysis of such patterns, we int...

Named entity recognition (NER) denotes the task to detect entities and their corresponding classes, such as person or location, in unstructured text data. For most applications, state of the art NER software is producing reasonable results. However, as a consequence of the methodological limitations and the well-known pitfalls when analyzing natura...

Dynamite adopts a multi-level task-driven approach to support event surveillance and time critical decision making for large premises, e.g. casinos or holiday resorts. The system integrates with a complex stream processing engine processing various heterogeneous streams using task-based aggregates. These task stream ensembles are processed in three...

Dynamite adopts a multi-level task-driven approach to support event surveillance and time critical decision making for large premises, e.g. casinos or holiday resorts. The system integrates with a complex stream processing engine processing various heterogeneous streams using task-based aggregates. These task stream ensembles are processed in three...

In this article, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which are significantly connected in time to quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an ex...

In many application areas, the key to successful data analysis is the integrated analysis of heterogeneous data. One example is the financial domain, where time-dependent and highly frequent quantitative data (e.g., trading volume and price information) and textual data (e.g., economic and political news reports) need to be considered jointly. Data...