Participatory design, beyond the local

This workshop aims at stimulating and opening a debate around the capacity of Participatory Design (PD) and other co-design approaches to deliver outcomes and methodologies that can have an impact and value for reuse well beyond the local context in which they were originally developed. This will be achieved by stimulating the submission of position papers by researchers from the PD community and beyond.These papers will be discussed during the workshop in order to identify challenges, obstacles but also potentials for scaling up PD processes and results from the local to the global.</p

A Survey of Location Prediction on Twitter

Locations, e.g., countries, states, cities, and point-of-interests, are central to news, emergency events, and people's daily lives. Automatic identification of locations associated with or mentioned in documents has been explored for decades. As one of the most popular online social network platforms, Twitter has attracted a large number of users who send millions of tweets on daily basis. Due to the world-wide coverage of its users and real-time freshness of tweets, location prediction on Twitter has gained significant attention in recent years. Research efforts are spent on dealing with new challenges and opportunities brought by the noisy, short, and context-rich nature of tweets. In this survey, we aim at offering an overall picture of location prediction on Twitter. Specifically, we concentrate on the prediction of user home locations, tweet locations, and mentioned locations. We first define the three tasks and review the evaluation metrics. By summarizing Twitter network, tweet content, and tweet context as potential inputs, we then structurally highlight how the problems depend on these inputs. Each dependency is illustrated by a comprehensive review of the corresponding strategies adopted in state-of-the-art approaches. In addition, we also briefly review two related problems, i.e., semantic location prediction and point-of-interest recommendation. Finally, we list future research directions.Comment: Accepted to TKDE. 30 pages, 1 figur

Sensemaking Practices in the Everyday Work of AI/ML Software Engineering

This paper considers sensemaking as it relates to everyday software engineering (SE) work practices and draws on a multi-year ethnographic study of SE projects at a large, global technology company building digital services infused with artificial intelligence (AI) and machine learning (ML) capabilities. Our findings highlight the breadth of sensemaking practices in AI/ML projects, noting developers' efforts to make sense of AI/ML environments (e.g., algorithms/methods and libraries), of AI/ML model ecosystems (e.g., pre-trained models and "upstream"models), and of business-AI relations (e.g., how the AI/ML service relates to the domain context and business problem at hand). This paper builds on recent scholarship drawing attention to the integral role of sensemaking in everyday SE practices by empirically investigating how and in what ways AI/ML projects present software teams with emergent sensemaking requirements and opportunities

An ontology co-design method for the co-creation of a continuous care ontology

Ontology engineering methodologies tend to emphasize the role of the knowledge engineer or require a very active role of domain experts. In this paper, a participatory ontology engineering method is described that holds the middle ground between these two 'extremes'. After thorough ethnographic research, an interdisciplinary group of domain experts closely interacted with ontology engineers and social scientists in a series of workshops. Once a preliminary ontology was developed, a dynamic care request system was built using the ontology. Additional workshops were organized involving a broader group of domain experts to ensure the applicability of the ontology across continuous care settings. The proposed method successfully actively engaged domain experts in constructing the ontology, without overburdening them. Its applicability is illustrated by presenting the co-created continuous care ontology. The lessons learned during the design and execution of the approach are also presented

The ‘responsibility’ factor in imagining the future of education in China

Design and creativity have been a considerable force for improving life conditions. A lot of effort has been invested in explaining the design process and creativity mainly through the design thinking methodology, but design accountability and responsible actions in the design process are, yet, to be fully explored. The concept of design ethics is now increasingly scrutinized on both the level of business organization and of the individual designer. A 4-day design workshop that involved creativity techniques provided the base to explore responsibility in the fuzzy front end of the design process. The future of education in 2030 was defined as the workshop's theme and fifty-six students from China were asked to create detailed alternative scenarios. A number of imagination exercises, implementation of technological innovations and macro-environment evolutions employed in the workshop are discussed. The aim was to incite moral and responsible actions among students less familiar with creative educational contexts of student-led discovery and collaborative learning. This paper reflects on the use of creativity methods to stimulate anticipation in (non)design students