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Trends like digital transformation even intensify the already overwhelming mass of information knowledge workers face in their daily life. To counter this, we have been investigating knowledge work and information management support measures inspired by human forgetting. In this paper, we give an overview of solutions we have found during the last five years as well as challenges that still need to be tackled. Additionally, we share experiences gained with the prototype of a first forgetful information system used 24/7 in our daily work for the last three years. We also address the untapped potential of more explicated user context as well as features inspired by Memory Inhibition, which is our current focus of research.
In recent years there has been an increasing trend in which data scientists and domain experts work together to tackle complex scientific questions. However, such collaborations often face challenges. In this paper, we aim to decipher this collaborat
We now turn to understanding the impact that COVID-19 had on the personal productivity and well-being of information workers as their work practices were impacted by remote work. This chapter overviews peoples productivity, satisfaction, and work pat
A plain well-trained deep learning model often does not have the ability to learn new knowledge without forgetting the previously learned knowledge, which is known as catastrophic forgetting. Here we propose a novel method, SupportNet, to efficiently
We describe the current state and future plans for a set of tools for scientific data management (SDM) designed to support scientific transparency and reproducible research. SDM has been in active use at our MRI Center for more than two years. We des
Autonomous agents acting in the real-world often operate based on models that ignore certain aspects of the environment. The incompleteness of any given model---handcrafted or machine acquired---is inevitable due to practical limitations of any model