In an era characterized by rapid digital transformation, the convergence of technology and healthcare is redefining both clinical practices and patient experiences. The second edition of the Innovative Interfaces in Digital Healthcare (INI-DH) workshop seeks to gather innovators, healthcare practitioners, designers, and researchers to investigate the diverse applications of visual interfaces within the digital health domain.

The information published in newspapers reflects the opinions and viewpoints that society holds on the principal public issues. Some topics can be particularly sensitive to gender biases, such as technology, politics, or sports, where, despite the growing relevance of women, the media tends to focus on men as protagonists and sources of reference. When women do appear, they are not treated equally. Analyzing how the information is presented from a gender perspective is necessary to assess progress toward equality in the journalism sector and society at large. These analyses are very costly to produce due to the time required and the shortage of experts in the field, so they are not as frequent as would be ideal. In this paper, we introduce IRIS, a tool that helps experts identify gender biases in news publications. The tool is designed to process content qualitatively and quantitatively, using variables defined in collaboration with researchers with extensive experience in gender studies. This first version of IRIS aims to capture human expertise and automatically generate a basic report to present analysis results from a gender perspective.

In the last years, there has been an increasing amount of data published in different sources, formats, and structures that could be useful for various purposes: learning about a topic, discovering trends, and monitoring public opinion, among others. To facilitate access to this data and, more importantly, to identify the most interesting information in the set, in this poster, we present an interactive tool aimed at extracting and processing collections of unstructured text data to create a knowledge graph that users can explore and edit. The tool has been designed in three modules: gathering information, processing texts, building relations, and visualizing the knowledge base. The user can interact with these steps, particularly by exploring the visualization and changing the concepts and the relations using either a graphical or textual view.

In an era defined by digital transformation, the intersection of technology and healthcare is reshaping the landscape of medical practice and patient experience. The Innovative Interfaces in Digital Healthcare (INI-DH) workshop is at the forefront of this revolutionary evolution, addressing the key role of visual interfaces in healthcare. The workshop aims to bring together innovators, healthcare professionals, designers, and researchers to explore the multiple applications of visual interfaces in digital healthcare. Nine papers were accepted.

Moving to a responsible engineering educational approach is a trend nowadays since the artifacts created by engineers have an impact on society and the environment. Ethics has become a key learning outcome value by many accreditation bodies, but ethics education can be implemented in many different ways. This paper advocates for an educational approach not only based on the introduction of stand-alone ethics courses but also on pouring values throughout the curriculum in any courses related to creating technologies. We describe here two examples of assignments that follow a microscale embedded ethics approach and active learning tasks to engage students in the exploration of biases and ethical issues concerning user interface design and data visualizations, respectively. The first example has a hidden goal of identifying gender-based biases in websites by applying reverse design thinking techniques on existing websites. The second example uses three different tasks to explore and apply ethics in data integration and visualizations by designing multisensorial visualizations that could serve more diverse audiences, applying value-based design in a final project, and elaborating an essay on existing unethical AI-based tools. Both experiences, which students appreciated, helped to raise awareness of ethical issues and the responsibility of computer science engineers.

Though virtual reality has been used for more than one decade to support learning, technology is now mature and cheap enough, and students have the required digital fluency to reach real settings. Immersive technologies have also demonstrated that they not only are engaging, but they can also reinforce learning and improve memory. This work presents a preliminary study on the advantages of using an immersive experience to help young students understand genetic editing techniques. We have relied upon the CHIC Immersive Bubble Chart, a VR (Virtual Reality) multi-device visualization of the most relevant topics in the domain. We tested the CHIC Immersive Bubble Chart by asking a group of 29 students to explore the information space by interacting with two different devices: a desktop and a VR headset. The results show that they mainly preferred the VR headset finding it more engaging and useful. As a matter of fact, during the evaluation, the students kept exploring the space even after the assigned time slot.

Taxonomies are semantic resources that help to categorize and add meaning to data. In a hyperconnected world where information is generated at a rate that exceeds human capacities to process and make sense of it, such semantic resources can help to access relevant information more efficiently by extracting knowledge from large and unstructured data sets. Taxonomies are related to specific domains of knowledge in which they identify relevant topics. However, they have to be validated by experts to guarantee that its terms and relations are meaningful. In this paper, we introduce a semiautomatic taxonomy generation tool for supporting domain experts in building taxonomies that are then used to automatically create semantic visualizations of data. Our proposal combines automatic techniques to extract, sort and categorize terms, and empowers domain experts to take part at any stage of the process by providing a visual edition tool. We tested the tool’s usability in two use cases from different domains and languages. Results show that all the functionalities are easy to use and interact with. Lessons learned from this experience will guide the design of a utility evaluation involving domain experts interested in data analysis and knowledge modeling.

Social networks are a subject of great interest worldwide. Year after year we have experienced an increase in the number of new users and, even, the creation of new technologies (i.e. augmented reality, 360º cameras, …) and new social networks. However, this phenomenon is contrasted with the appearance of automatic programs (bots) and fake news that can affect the quality of published information. This paper presents the state of the art of the quality of the information found in different social networks. In addition, we propose a series of learnt lessons to be followed in order to develop a theoretical application that measures the quality of a user generated information for a given event.

In this paper, we propose a tool to build taxonomies in a semi-automatic way. Taxonomies are key structures to model and categorize knowledge focusing on the semantics. Designing a taxonomy means finding meaningful concepts respect to a domain of application. This complex task requires the involvement of domain experts to define a representative dictionary. To keep a human-in-the-loop approach, taxonomies have been mostly created manually with a great cost in time and resources. Our goal is to design a general-purpose and multi-language tool that will automatize the process of building a taxonomy from a document corpus. The proposed architecture can be used in different domains, as well as in different languages.

Third generation devices, such as smartphones, have the possibility of knowing the position of the user. By combining time, position and data in the Cloud it is possible to make smart deductions as to what information the user needs. These deductions can be performed by an automated assistant that have access to the user's e-mail and SMS messages, calendar, phone book, notes, etc., as well as to the position of the user. The assistant can present the information in an "I feel lucky" display on the user's smartphone. These concepts have been evaluated in a case study with a group of students, simulating the output of such an interface.