Guided Interaction Exploration and Performance Analysisin Artifact-Centric Process Models

Artifact-centric process models aim to describecomplex processes as a collection of interacting artifacts.Recent development in process mining allow for the dis-covery of such models. However, the focus is often on therepresentation of the individual artifacts rather than theirinteractions. Based on event data, composite state machi-nes representing artifact-centric processes can be discov-ered automatically. Moreover, the study provides ways ofvisualising and quantifying interactions among differentartifacts. For example, strongly correlated behaviours indifferent artifacts can be highlighted. Interesting correla-tions can be subsequently analysed to identify potentialcauses of process performance issues. The study provides astrategy to explore the interactions and performance dif-ferences in this context. The approach has been fullyimplemented as a ProM plug-in; the CSM Miner providesan interactive artifact-centric process discovery toolfocussing on interactions. The approach has been evaluatedusing real life data, to show that the guided exploration ofartifact interactions can successfully identify process per-formance issues

Guided Interaction Exploration in Artifact-centric Process Models

Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the discovery of such models. However, the focus is often on the representation of the individual artifacts rather than their interactions. Based on event data we can automatically discover composite state machines representing artifact-centric processes. Moreover, we provide ways of visualizing and quantifying interactions among different artifacts. For example, we are able to highlight strongly correlated behaviours in different artifacts. The approach has been fully implemented as a ProM plug-in; the CSM Miner provides an interactive artifact-centric process discovery tool focussing on interactions. The approach has been evaluated using real life data sets, including the personal loan and overdraft process of a Dutch financial institution.Comment: 10 pages, 4 figures, to be published in proceedings of the 19th IEEE Conference on Business Informatics, CBI 201

Advancements and Challenges in Object-Centric Process Mining: A Systematic Literature Review

Recent years have seen the emergence of object-centric process mining techniques. Born as a response to the limitations of traditional process mining in analyzing event data from prevalent information systems like CRM and ERP, these techniques aim to tackle the deficiency, convergence, and divergence issues seen in traditional event logs. Despite the promise, the adoption in real-world process mining analyses remains limited. This paper embarks on a comprehensive literature review of object-centric process mining, providing insights into the current status of the discipline and its historical trajectory

Interactions in Visualizations to Support Knowledge Activation

Humans have several exceptional abilities, one of which is the perceptual tasks of their visual sense. Humans have the unique ability to perceive data and identify patterns, trends, and outliers. This research investigates the design of interactive visualizations to identify the benefits of interacting with information. The research question leading the investigation is how does interacting with visualizations support analytical reasoning of emergent information to activate knowledge? The study uses the theory of distributed cognition and human-information interaction to apply the design science research framework. The motivation behind the research is to identify guidelines for interactive visualizations to enhance a user’s ability to make decisions in dynamic situations and apply knowledge gleaned from the visualization. An experiment is used to analyze the use of an interactive dashboard in a dynamic decision-making situation. The results of this experiment specifically look at the combination of interactions as they support the distribution of cognition over three spaces of a human-visualization cognitive system. The results provide insight into the benefits that interactions have for enhancing analytical reasoning, expanding the use of visualizations beyond communicating or disseminating information. Providing a broad range of interactions that work with multiple views of information increases the opportunities that users have to complete tasks. This research contributes to the information visualization discipline by expanding the focus from representing data to representing and interacting with information. Secondly, my results provide an example of a qualitative assessment based on the value of visualization, in comparison to traditional usability assessment

Designing Attention-Centric Notification Systems: Five HCI Challenges

Through an examination of the emerging domain of cognitive systems, with a focus on attention-centric cognitive systems used for notification, this document explores the human-computer interaction challenges that must be addressed for successful interface design. This document asserts that with compatible tools and methods, user notification requirements and interface usability can be abstracted, expressed, and compared with critical parameter ratings; that is, even novice designers can assess attention cost factors to determine target parameter levels for new system development. With a general understanding of the user tasks supported by the notification system, a designer can access the repository of design knowledge for appropriate information and interaction design techniques (e.g., use of color, audio features, animation, screen size, transition of states, etc), which have analytically and empirically derived ratings. Furthermore, usability evaluation methods, provided to designers as part of the integrated system, are adaptable to specific combinations of targeted parameter levels. User testing results can be conveniently added back into the design knowledge repository and compared to target parameter levels to determine design success and build reusable HCI knowledge. This approach is discussed in greater detail as we describe five HCI challenges relating to cognitive system development: (1) convenient access to basic research and guidelines, (2) requirements engineering methods for notification interfaces, (3) better and more usable predictive modeling for pre-attentive and dual-task interfaces, (4) standard empirical evaluation procedures for notification systems, and (5) conceptual frameworks for organizing reusable design and software components. This document also describes our initial work toward building infrastructure to overcome these five challenges, focused on notification system development. We described LINK-UP, a design environment grounded on years of theory and method development within HCI, providing a mechanism to integrate interdisciplinary expertise from the cognitive systems research community. Claims allow convenient access to basic research and guidelines, while modules parallel a lifecycle development iteration and provide a process for requirements engineering guided by this basic research. The activities carried out through LINK-UP provide access to and interaction with reusable design components organized based on our framework. We think that this approach may provide the scientific basis necessary for exciting interdisciplinary advancement through many fields of design, with notification systems serving as an initial model. A version of this document will appear as chapter 3 in the book Cognitive Systems: Human Cognitive Models in Systems Design edited by Chris Forsythe, Michael Bernard, and Timothy Goldsmith resulting from a workshop led by the editors in summer 2003. The authors are grateful for the input of the workshop organizers and conference attendees in the preparation of this document

Towards Design Principles for Data-Driven Decision Making: An Action Design Research Project in the Maritime Industry

Data-driven decision making (DDD) refers to organizational decision-making practices that emphasize the use of data and statistical analysis instead of relying on human judgment only. Various empirical studies provide evidence for the value of DDD, both on individual decision maker level and the organizational level. Yet, the path from data to value is not always an easy one and various organizational and psychological factors mediate and moderate the translation of data-driven insights into better decisions and, subsequently, effective business actions. The current body of academic literature on DDD lacks prescriptive knowledge on how to successfully employ DDD in complex organizational settings. Against this background, this paper reports on an action design research study aimed at designing and implementing IT artifacts for DDD at one of the largest ship engine manufacturers in the world. Our main contribution is a set of design principles highlighting, besides decision quality, the importance of model comprehensibility, domain knowledge, and actionability of results

Exploring Natural User Abstractions For Shared Perceptual Manipulator Task Modeling & Recovery

State-of-the-art domestic robot assistants are essentially autonomous mobile manipulators capable of exerting human-scale precision grasps. To maximize utility and economy, non-technical end-users would need to be nearly as efficient as trained roboticists in control and collaboration of manipulation task behaviors. However, it remains a significant challenge given that many WIMP-style tools require superficial proficiency in robotics, 3D graphics, and computer science for rapid task modeling and recovery. But research on robot-centric collaboration has garnered momentum in recent years; robots are now planning in partially observable environments that maintain geometries and semantic maps, presenting opportunities for non-experts to cooperatively control task behavior with autonomous-planning agents exploiting the knowledge. However, as autonomous systems are not immune to errors under perceptual difficulty, a human-in-the-loop is needed to bias autonomous-planning towards recovery conditions that resume the task and avoid similar errors. In this work, we explore interactive techniques allowing non-technical users to model task behaviors and perceive cooperatively with a service robot under robot-centric collaboration. We evaluate stylus and touch modalities that users can intuitively and effectively convey natural abstractions of high-level tasks, semantic revisions, and geometries about the world. Experiments are conducted with \u27pick-and-place\u27 tasks in an ideal \u27Blocks World\u27 environment using a Kinova JACO six degree-of-freedom manipulator. Possibilities for the architecture and interface are demonstrated with the following features; (1) Semantic \u27Object\u27 and \u27Location\u27 grounding that describe function and ambiguous geometries (2) Task specification with an unordered list of goal predicates, and (3) Guiding task recovery with implied scene geometries and trajectory via symmetry cues and configuration space abstraction. Empirical results from four user studies show our interface was much preferred than the control condition, demonstrating high learnability and ease-of-use that enable our non-technical participants to model complex tasks, provide effective recovery assistance, and teleoperative control