Nowadays, we are surrounded by technology that assists us in our everyday life. We use GPS devices to navigate from A to B, we use all kind of sensors (e.g., in a smart home environment) that detect our activities, we query the WWW for information while on the go and we use all kinds of devices and software to communicate with our friends and family and share opinions, pictures, etc. With today’s technology, we have the capability to automatically record at largescale the places that we have been to, things we have seen, people we communicate with and how active we are we’re already creating a constant stream of data that reveals many aspects of our lives.
This creation of constant data streams offers new possibilities for personalization but the resulting data volume raises new challenges. Analyzing this large data corpus may enable us to better understand ourselves: What are my habits and interests? Or, even help us answer more specific questions: Do I live a healthy life? Answering such questions can lead to a more self-aware lifestyle. One big challenge is the creation and management of longterm, even life long, user models. These must capture salient aspects about the user over very long periods of time, possibly spanning periods from early childhood into old age. These models have to handle changing interests over time. Also, such life-long user models have to be usable by different applications. Other challenges pertain to processing big personal data and identifying user interests, skills etc. and their usage in real world systems like health or recommendation systems. Following the first two successful Workshops on Lifelong User Modelling which were held in conjunction with UMAP 2009 and 2013, respectively, this workshop aims to engage researchers from both user modelling and ubiquitous computing communities to discuss emerging research trends in this field.