Cathrine Seidelin - Academia.edu (original) (raw)

Papers by Cathrine Seidelin

BCS Learning & Development, 2018

The term Human-Data Interaction (HDI) conceptualizes the growing importance of understanding how ... more The term Human-Data Interaction (HDI) conceptualizes the growing importance of understanding how people need and desire to use and interact with data. Previous HDI cases have mainly focused on the interface between personal health data and the healthcare sector. This paper argues that it is relevant to consider HDI at an organisational level and examines how HDI can look in such a context, where data and data maintenance are core assets and activities. We report on initial findings of a study of a knowledge-broker organisation, where we follow how data are produced, shared, and maintained in a cross-organisational context. We discuss similarities and differences of HDI around personal health data and cross-organisational data maintenance. We propose to extend the notion of HDI to include the complexity of cross-organisational data work.

International journal of human-computer studies, Nov 1, 2020

Abstract The rise of Big Data and data science has prompted a focus on data as an essential compo... more Abstract The rise of Big Data and data science has prompted a focus on data as an essential component of making and innovating data-based services. Traditionally, however, digital data has not been object to co-design as have other physical or functional dimensions of IT application design. This is problematic, because it hinders domain experts who are not IT professionals from taking part in the discussions and design of the data-based services they use and provide. We argue that to address this challenge, it is necessary to empower such domain experts to be able to consider data as an object of design, so they may contribute their expertise to the design of data-based services and their underlying data structures. This paper describes how data may be foregrounded as an explicit element of design that support domain experts’ understanding of data as something that can be designed. We present a detailed interaction analysis of video recordings of three collaborative design workshops, in which we propose a form of data notation and two data representations. We find that data may become an object of design for domain experts when tangible and flexible representations of data are used. Based on our findings, we discuss five lessons learned for foregrounding data in co-design. Together, these provide practical insights for future work.

Organisations are looking for new service offers through innovative use of data, often through a ... more Organisations are looking for new service offers through innovative use of data, often through a Service Design approach. However, current Service Design tools conceal technological aspects of service development like data and datasets. Data can support the design of future services but is often not represented or rendered as a readily workable design material. This paper reports on an early qualitative study of the tools used to work with data and analytics in a medium-sized organisation. The findings identify the current representations of data and data analytics used in the case organisation. We discuss to which extend the available representations of data and data analytics support data-driven service innovation. A comparison of our findings and current Service Design representations show that Service Design lack to represent data as design material. We propose the notion of expansiveness as a criterion to evaluate future data representations for data-driven Service Design.

In recent years, local government has been undergoing changes which are strongly influenced by th... more In recent years, local government has been undergoing changes which are strongly influenced by the growing digitization of governmental operations. In this paper, we expand on the concepts of Digital Era Governance and its successor, Essentially Digital Government, by introducing the concept of Algorithmic Bureaucracy, which looks at the impacts of artificial intelligence on the socio-technical nature of public administration. We report on a mixed-method study, which focused on how the growth of data science is changing the ways that local government works in the United Kingdom. Under Algorithmic Bureaucracy, the direct and indirect effects of public administrative changes on the level of social problem solving may become positive in two cases: 1) where through artificial intelligence and isocratic administration the explainability of algorithmic processes increases individual and staff competence, and 2) where algorithms take on some of the role of processing institutional and policy complexity much more effectively than humans.

Proceedings of the ACM on Human-Computer Interaction

The question of how to develop and maintain appropriate, socially informed and sophisticated infr... more The question of how to develop and maintain appropriate, socially informed and sophisticated infrastructural systems is an ongoing concern for CSCW. Information infrastructure development efforts are usually large endeavors that involve many stakeholders, including several organizations that need to interoperate with legacy systems. Projects typically take several years to develop. The duration, variety, and sites of engagement in the development of information infrastructures can be challenging to approach with typical CSCW approaches. In this paper, we compare and analyze our varied experiences in order to generate lessons learned based on being embedded for three or more years as action researchers and ethnographers in infrastructure development projects in the domains of traffic engineering, vocational education, and ocean science. Drawing upon these experiences, as well as literature in infrastructure studies, design methodologies, and organizational studies, we extract guidanc...

[ ] With Design: Reinventing Design Modes, 2022

The internet has long been a core infrastructure especially for the western societies. In the las... more The internet has long been a core infrastructure especially for the western societies. In the last decade, the usage of the internet changed from a mainly communication infrastructure giving mainly access to static information to become a platform to full-scale applications implemented as services. Even more recently we can observe a growing use of the internet to collect and provide data: social media platforms and search engines collect, use and sell data about their usage and users; online shops use data to recommend goods to the buyer; municipalities and other public organisations provide data through open data interfaces so it can be used by companies, e.g. to provide advice for car drivers searching for a parking lot. The data infrastructure making data accessible, though, requires IT expertise. In this position paper we explore the implication of this development from a participatory design perspective and argue that we need to engage in infrastructuring in order to make the common data a common good. Data as infrastructure Google maps does not only provide information of how to get from A to B, but also uses data collected from service users to inform about traffic density and expected travel times so that commuters can select a different route or time for their trip; Amazon and other online shops use past data about shopping patterns to recommend books and goods for purchase; traffic management systems use historical and current data about traffic to regulate speed on highways. These examples have in common that data is not any longer (only) used to store and retrieve information about specific persons, situations or events, but as infrastructure based on which services for the users or the public are provided. Similar, many municipalities and public agencies today use data to inform decision making: the most cited case might be New York City directing fire inspectors to addresses where fires with casualties are likely to happen (Hofman 2012). However, more and more municipalities make part of their data available as open data. Such open data can be anything from statistic data about socioeconomic status of citizens, geospatial data about the physical infrastructures like streets and parks, brought to you by CORE View metadata, citation and similar papers at core.ac.uk

The personal and professional support and encouragement of so many wonderful people made this dis... more The personal and professional support and encouragement of so many wonderful people made this dissertation possible. First and foremost, I would like to thank Industriens Uddannelser, Dansk Industri, Dansk Metal and 3F for having the vision to initiate and carry out this Industrial PhD project. I would also like to thank Innovation Fund Denmark and the Industry's Foundation for Education and Collaboration who financed this project. I am very thankful to all my colleagues, who showed great curiosity and participated in research activitiesusually without knowing what the outcome would be. This dissertation simply would not have been possible without you! Also, a heartfelt thank you to my dear colleague and co-author Stine Moeslund Sivertsen. Your endless curiosity, creativity, and optimism are invaluable. Moreover, I would like to thank my industry supervisors: Henrik Amdi Madsenthank you for your visionary outlook, constant encouragement and inspiring discussions; Louise Sonne Dyreborgthank you for always looking after me, and for your insightful advice. I would like to thank my primary academic supervisor, Prof. Yvonne Dittrich. Throughout this process, you have always gone above and beyond to support me and my work. Thank you for your our many rewarding discussions, your helpful guidance, and for challenging me. I would also like to thank my academic co-supervisor, Assoc. Prof. Erik Grönvall, for our inspiring discussions and valuable feedback. I am also much indebted to Prof. Irina Shklovski, Asst. Prof. Christian Østergaard Madsen, and Prof. Minna Isomursu for their thoughtful comments and suggestions during my midway evaluation. You feedback has contributed greatly to the development of my arguments. Next, I would like to thank the people all over the world who have contributed and helped refine this work. I would like to thank the Oxford Internet Institute, Oxford University, for hosting me during my research abroad stay. I would especially like to thank Prof. Jonathan Bright, Bharath Ganesh, and Thomas Vogl for bringing me on board the Data Science for Local Government study, and for your excellent collaborationalso after I left Oxford. Furthermore, I would like to thank the Human Centred Design and Engineering Department, University of Washington, for hosting me during my second research stay abroad. A special thanks to Assoc. Prof. Charlotte P. Lee and the CSC Lab for fruitful discussions, which contributed to the refinement of my arguments. Thanks to all the people who provided feedback and engaged in interesting discussions during courses, doctoral consortiums, and research visits. I would also like to thank my fellow doctoral candidates at ITU and abroadour support for one another on our individual but somewhat parallel journeys has been a great help to me. Finally, I would like to extend my deepest thanks to my great friends, who have listened and have kept me sane during this process, and to my dear family for their endless support and encouragement. Last but not least, a heartfelt thanks to Jakobmeeting you in Oxford has turned this journey into an adventure.

Proceedings of the ACM on Human-Computer Interaction, 2022

As more and more governments adopt algorithms to support bureaucratic decision-making processes, ... more As more and more governments adopt algorithms to support bureaucratic decision-making processes, it becomes urgent to address issues of responsible use and accountability. We examine a contested public service algorithm used in Danish job placement for assessing an individual's risk of long-term unemployment. The study takes inspiration from cooperative audits and was carried out in dialogue with the Danish unemployment services agency. Our audit investigated the practical implementation of algorithms. We find (1) a divergence between the formal documentation and the model tuning code, (2) that the algorithmic model relies on subjectivity, namely the variable which focus on the individual's self-assessment of how long it will take before they get a job, (3) that the algorithm uses the variable "origin" to determine its predictions, and (4) that the documentation neglects to consider the implications of using variables indicating personal characteristics when predic...

Service design (SD) is acknowledged as an approach that can help organisations to address service... more Service design (SD) is acknowledged as an approach that can help organisations to address service innovation. However, organisations are struggling to build design capabilities and develop sustainable SD cultures within the organisations. This paper focuses on this central challenge by exploring how a small and medium-sized “non-design-intensive organisation” can integrate SD both as a way to develop internal design capabilities and as an approach to service innovation. We report on an action research study in which we initiated seven SD micro cases. The findings show how our designed SD learning activities developed autonomous SD initiatives within the organisation, and thus over time fostered a sustainable SD culture in this context. Based on our findings, we conclude that organisational appropriation of SD tools and methods is crucial for an organisation’s ability to build and sustain capabilities which can foster an SD culture.

Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing, 2018

Data has become a core asset for organizations. However, the data infrastructures, which makes da... more Data has become a core asset for organizations. However, the data infrastructures, which makes data accessible often require IT expertise, which consequently places high demands on organiza-tions' computational knowledge and skills. This paper reports on preliminary results of an action research intervention that questions how data can become an accessible enabler for service innovation in small and medium-sized organiza-tions (SMEs). On this basis, I highlight three in-frastructuring challenges for data infrastructures that are relevant from a Participatory Design (PD) perspective. The paper concludes by suggesting future work and advice sought.

Data science provides powerful tools and methods. CSCW researchers have contributed insightfulstu... more Data science provides powerful tools and methods. CSCW researchers have contributed insightfulstudies of conventional work-practices in data science - and particularly machine learning. However,recent research has shown that human skills and collaborative decision-making, play important rolesin defining data, acquiring data, curating data, designing data, and creating data. This workshopgathers researchers and practitioners together to take a collective and critical look at data sciencework-practices, and at how those work-practices make crucial and often invisible impacts on theformal work of data science. When we understand the human and social contributions to data sciencepipelines, we can constructively redesign both work and technologies for new insights, theories, andchallenges.

This note explores how data work takes place in a public sector arena. We report on findings from... more This note explores how data work takes place in a public sector arena. We report on findings from a 3-year research project with a Danish organisation, which, amongst other things, aimed to improve current data practices in the organisation. We make use of the notion of ‘social arenas’ as a lens to understand the complex setting the organisation is situated in. We find that data work in this context takes place among multiple stakeholders and requires cooperation across organisational boundaries. Moreover, changes in data practices in one site changes cooperation among multiple stakeholders in the arena. Additionally, we develop a diagram of this complex setting, which constitutes an analytical tool that supports our understanding of the site (or sites) of intervention where data work is examined. Our study contributes to the field of CSCW by proposing and showing how the notion of sub-arena helps to comprehend the cooperation and interaction within the surprisingly complex public s...

Communications in Computer and Information Science

Proceedings of the 9th International Conference on Communities & Technologies - Transforming Communities

Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society

Public Administration Review