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The adoption of Artificial Intelligence (AI) by the public sector has the potential to improve service delivery. However, the risks related to AI are significant and citizen concerns have halted several AI initiatives. In this paper we report findings from an empirical study on citizens´ attitudes towards AI use in public services in Norway. We found a generally positive attitude and identified three factors contributing to this: a) the high level of trust in government; b) the reassurance provided by having humans in the loop; c) the perceived transparency into processes, data used for AI models and models´ inner workings. We interpret these findings through the lens of social contract theory and show how the introduction of AI in public services is subject to the social contract power dynamics. Our study contributes to research by foregrounding the government-citizen relationship and has implications for public sector AI practice. Paid open access

Research methods are part and parcel of good research. Despite this, we often teach research methods in an ad hoc manner and do not reflect on relevant pedagogical aspects. This situation is changing due to the introduction of dedicated research methods courses as part of a transferable skills agenda in many universities. To address pedagogical aspects of teaching methods in IS, we organized a workshop during the 10th Scandinavian Conference on Information Systems (SCIS/IRIS). Our goal was to create a community of practice among supervisors and teachers of research methods in IS. In this paper, we present our findings from the workshop presentations and discussions. Three main themes emerge from our workshop: 1) Coping with student motivational aspects of learning research methods at micro and macro levels, 2) Challenges related to course design for different institutional contexts, and 3) The challenging interplay between IS theory and empirical data when teaching research methods. We discuss these themes and their relation to the field of IS. We propose some future research topics for the community.

Researchers of Information Systems have long demonstrated that the teaching of research methods hinges on the dynamic interplay between theory and practice. However, grasping the role of theory in both the process (research design) and products (reading and writing articles) of research is challenging for teachers and, crucially, their students. This project contributes to the pedagogical discourse on qualitative research methods in Information Systems. It proposes the prototype of a framework in the shape of an agile lecture sequence for making explicit the role of theory across the research process when teaching research methods in Information Systems. The proposed framework is based on a constructivist approach, recognizing that students co-construct their knowledge recursively through the interplay with the socio-cultural context. Copyright (c) 2020 Elena Parmiggiani Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Open Access. CC BY-NC-ND license (Attribution-NonCommercial-NoDerivatives.

This thesis investigates the development of ICT solutions for performing real-time subsea environmental monitoring during oil and gas offshore operations. The research is based on a three-year case study of an international oil and gas company headquartered in Norway. The thesis is specifically focused on aspects of integration: how new tools, systems, and approaches are developed, and how existing ones are adapted to fit the existing systems and practices of the oil and gas company. The thesis has three goals. First, it analyzes how real-time environmental monitoring emerges as a distributed, interacting, and interconnected sociotechnical network (information infrastructure). Second, it identifies how the company’s initiatives are currently changing the representations of subsea environmental risk in remote and previously inaccessible areas like the Arctic region. Third, it reflects on the research methodology to address such a spatially distributed and long-term setting. On the theoretical level this work aims to contribute to the field of Information Systems and, marginally, to Computer-supported cooperative work. It is also inspired by Science and Technology Studies. A theoretical framework is developed connecting contributions from these three streams of literature in order to characterize the co-evolution of environmental monitoring infrastructures and their phenomenon of interest, environmental risk. This evolving relationship shows that, on the one hand, the perception of environmental risk as a problem is affected by the integration mechanisms that generate new knowledge. On the other hand, new conceptions of environmental risk have consequences for the maintenance and upgrade of environmental monitoring infrastructures. I call this process infrastructuring. The thesis provides a vivid empirical illustration of how the relationship between environmental risk and integration strategies unfolds in offshore environmental monitoring. By merging the theoretical framework and the empirical case, I argue in favor of a flexible understanding of the development of complex systems in organizational settings. Studies of infrastructure should account for the existence of pragmatic approaches to face persistent uncertainty and the fluid relationship between situated usefulness and a cross-geographical dimension. In line with existing debates in the literature, I demonstrate that the traditionally bounded distinctions of system design/development/implementation and of users/designers must be overtaken when studying infrastructures. On the methodological level, this thesis therefore advocates a deeper empirical analysis of the unfolding of infrastructures in organizational realities.

Digitale plattformer finnes overalt rundt oss. De tilbyr tjenester som mange bruker daglig. Konkurranse, brukerbehov og et plattformøkosystem i stadig endring tydeligjør verdien av tjenesteinnovasjon. Det finnes et mangfold av forskjellige designrammeverk og teknikker som brukes for å utføre denne innovasjonen. Design science er nødvendig mer enn noen gang ettersom problemer i tjenesteinnovasjon utforskes i stadig nye miljøer. Å bruke velkjente og utprøvde metoder på eksisterende designrammeverk kan forbedre deres evne til å takle kompleksiteten til problemene som digitale plattformøkosystemer presenterer. Data science er et modent felt og tilbyr metoder som synergi godt med datagenereringen digitale plattformer kan tilby. Målet med dette studiet er å gi innsikt i hvordan digitale transaksjonsplattformer utfører tjenesteinnovasjon gjennom design science. Det praktiske målet med denne studien er å se etter sammenheng mellom brukervalg av påloggingsløsning og betalingsalternativ i en nettbutikk. Nettbutikken fungerer som designgjennstanden og målet for designrammeverket for design science. Data science testes som et verktøy for å utføre evaluering av designgjennstanden i designrammeverket ved å samle inn kvantitative data om bruken av komponentene i appen. I tillegg brukes kvalitative data fra spørreskjemaer til identifisere relevans og bekrefte funn av dataanalyse. Digital platforms are found everywhere around us. They provide services which many use on a daily basis. Competition, user needs and an ever-changing platform ecosystem makes the importance of service innovation abundantly clear. There exists a plethora of different design frameworks and techniques utilized to perform this innovation. Design science is needed more than ever as the problems of service innovation become more diverse and expand and create new environments. Applying rigorous methods to existing design frameworks can enhance their ability to tackle the complexity of the problems which digital platform ecosystems present. Data science is a mature field and provides rigorous methods which synergises well with the data generation digital platforms can provide. The aim of this study is to provide insight into how digital transaction platforms perform service innovation through design science. The practical goal of this study is to look for correlation and possible synergies between user choice of sign-in solution and payment option in an eCommerce store environment. The eCommerce store acts as the artifact and the target of the design science research framework. Data science is tested as a tool for performing evaluation of the artifact in the design science research framework by gathering quantitative data on the use of the app components. Supplemental qualitative data from questionnaires will identify relevance and confirm findings of data analysis.

Miljødata blir brukt til å informere, begrunne, og evaluere miljøpolitikk. Dermed er det avgjørende at denne dataen både er av høy kvalitet, og at den er presis i sin gjenspeiling av den virkelige verden. Hvordan forskere oppnår denne kvaliteten på data har blitt undersøkt fra tekniske og praktiske perspektiv, med lite fokus på innvirkning fra forskere og deres interaksjon. Tidligere litteratur har identifisert utfordringer forskere opplever i å forberede og dele data, der fokuset er eksterne innflytelser slik som mangel på ressurser og utfordrende retningslinjer. Det er derimot lite fokus på interne prosesser og hvordan disse påvirker hverandre, samt hvilken rolle eksterne innflytelser har på forberedning og deling av data. Dette prosjektet består av en fortolkende case-studie. Prosjektet har som mål å bidra med ny empirisk innsikt i hvordan samarbeid og koordinativ praksis i dataforberedelse og datadeling foregår på norske miljøforskningsinstitutt, og hvordan denne praksisen påvirker datakvalitet. Case-studien er basert på kvalitative data i form av intervjuer, observasjoner, og dokumentasjon. Funnene i studien identifiserer viktige roller og avhengigheter i dataforberedelsesprosesser. Videre antyder funnene at dataforberedelse blir påvirket av flere typer avhengigheter, og at disse videre påvirker datakvalitet. Funnene viser også at forskere fra norske forskningsinstitusjoner ikke alltid opplever press i form av retningslinjer og annen politikk i like stor grad som tidligere forskning viser, som kan være tegn på at innføring og håndheving av disse varierer i stor grad, samt er avhengig av lokal politikk. Environmental data provides us with knowledge about the state of our environment, and is used as a foundation for informing, establishing, and revising environmental policy. Thus, the quality of this data, and the ability of this data to reflect the real world are crucial for policy decision-makers. Still, there seems to be a gap in existing literature when it comes to how this quality is achieved through relations researchers have with one another and their data, with most studies focusing on technical and practical measures. Previous literature has identified challenges in preparing and sharing environmental data, with the focus being on external influences such as resources or policy. With existing studies documenting these interrelationships, it seems fitting to look at this from a different perspective, exploring the internal processes of environmental data work, how they influence each other, and how external factors play into the preparation and sharing of data. This project consists of an explanatory case study, with an interpretive approach. The aim of the study is to contribute with empirical data on the coordinative and cooperative practices of researchers preparing and sharing data in Norwegian environmental research stations, and how these practices influence data quality. The case study draws on qualitative data in the form of interviews, observations and document studies. The findings identify key roles and dependencies in environmental data preparation. Furthermore, the findings suggest that data preparation is a cooperative activity that relies on multiple dependencies to function, and that the quality of the resulting data is a product of these dependencies. Additionally, the findings suggest that data sharing activities in Norwegian non-profit organizations are often much less pressured by regulatory measures in contrast to previous literature on the topic, suggesting that there is substantial variance in matters of local policy implementation.

Information systems (IS) implementation often aims to ensuring user satisfaction. However, achieving such user-centredness has remained ambiguous and challenging, and the results are not always those that were promised. This may result from several views and fluctuating and implicitly defined concepts. While some premises have been identified, they seem to mostly concern easily manageable settings where the number of users is limited, or where the possibility to tailor the system is significant. Especially in a large-scale system's implementation user-centredness seems to be fuzzy. In this paper we illustrate how user-centredness unfolds in a large scale IS implementation. We conduct a qualitative case study to see what occurs when the efforts are declared user-centred. By interviewing 13 central actors from a local developer organization, we learnt that user-centredness in such context is essentially the result of joint efforts thus necessitating that each party carries out their responsibility for user-centredness and engages in collaboration with others. The paper contributes to research by sharing empirically grounded findings to be used to extend the discussion on user-centredness. publishedVersion

Verifiable credentials, coupled with decentralized ledger technologies, have been potential providers of trustworthy digital identity for individuals, organizations, and other entities, and thus, potential enablers of trustful digital interactions. The rapid development of this technology—called self-sovereign identity (SSI)—and the ecosystems built around it have been fostered even more by the societal needs stemming from the current pandemic crisis, when governments, non-profit organizations, businesses, and individuals are working together on different aspects of SSI to enable mainstream adoption. In this study, we build on rich qualitative data gathered from SSI practitioners to give a fresh overview of the perceived benefits and challenges of SSI. The paper advances research on the domain of SSI adoption and provides valuable insights into the feasibility of SSI for practitioners both in the private and public sectors peerReviewed

Due to COVID-19, companies were forced to adopt new work processes, and reduce modern work environments such as collaboration spaces. Professionals from many fields were forced to work remotely, almost overnight. Little is known about the impact of such non-volunteer remote work on productivity, stress, and other key aspects of work performance. To further our understanding of the impacts of this situation and remote work in general, we conducted an exploratory study by studying 28 knowledge work professionals (researchers, software developers, interior designers, service designers, and development consultants) from the viewpoint of perceived productivity and aspects affecting it in this unusual setting. Early results showed the positive influence of self-efficacy and teamwork on productivity during remote work, while no moderating effect of measured physical stress on productivity either through the intrinsic or social factor was present. peerReviewed

Bruken av intelligente teknologier, IoT enheter, i forskning har bidratt til å gjøre arbeid med miljøforskning lettere og mer tilgjengelig, da det er mulig å måle nesten det en vil til en lav pris. Eksempler på intelligente teknologier er sensorer som måler temperatur, fuktighet eller trykk, kameraer og akustiske enheter slik som ekkolodd, og de er intelligente fordi de kan levere data automatisk uten behov menneskelig interaksjon. Automatiske innsamlinger av sanntidsdata, ofte fra enheter med ulik kvalitet og følsomhet, fører imidlertid til lagring av omfattende mengder med rådata. Som et resultat av dette må forskere kontinuerlig forsikre seg om at enhetene er kalibrerte, og gjøre dataene pålitelige, lesbare og meningsfulle med hensyn til konteksten. For å gjøre forskning gjennomførbart, er forskningsstasjoner – som også kan bli referert til som forskningsinfrastrukturer – noen ganger avhengige av finansiering via styrende institusjoner som for eksempel ESFRI og Forskningsrådet i Norge. For å motta finansiering – og med et økt fokus på åpen datadeling mellom forskningsinfrastrukturer, stilles det høyere krav til datadokumentasjon i henhold til de standarder og krav som myndighetene setter. Dette er med på å påvirke forskeres datastyringsarbeid. Forskningen som er gjort i dette prosjektet har som mål å bidra med empirisk innsikt i hvordan intelligente teknolgier brukes på forskningsstasjoner for miljøovervåkning, og hvordan forskeres arbeid påvirkes av økt bruk av teknologi i overvåkning. Det er undersøkt hvordan forskere opplever retningslinjene satt av forskningsinstitusjoner om hvordan dataene skal dokumenteres, og hvordan deres dataarbeid må tilpasses deretter. Det er gjennomført et casestudie av utvalgte forskningsstasjoner for miljøovervåkning i Norge, og studien baserer seg på kvalitative data fra strukturerte og semi-strukturerte intervjuer og relevante dokumenter fra myndighetene slik som strategidokumenter, retningslinjer og veikart. Funnene er basert på informasjon fra intervjuer av informanter som til daglig arbeider på forskningsstasjoner for miljøovervåkning som dataledere, forskningssjefer, forskningskoordinatorer eller miljøforskere. Funnene viser at IoT basert miljøovervåkning er muliggjort av datastyringsarbeid, med etablerte prosesser for å sikre at store sett av rådata blir gjort pålitelige, lesbare og meningsfulle for å støtte fremtidig gjenbruk og tolkning. Prosessene er påvirket av retningslinjer, prosedyrer og standarder for hvordan dataene skal samles inn og håndteres, som er med på å påvirke forskeres arbeidspraksiser. På grunn av begrensninger i tid, finansiering og ressurser, viser funnene imidlertid at det kan være vanskelig å ha ønsket kvalitet i forskernes vitenskapelige arbeid. The use of intelligent technologies, particularly IoT devices, in research has contributed to more accessible and available monitoring of the environment with the possibility of monitoring almost anything with low costs. Examples of intelligent technologies used in environmental research are sensors monitoring temperature, humidity or pressure, cameras, and acoustic devices like echo sounders. The devices are intelligent because they can automatically deliver data without human interaction. However, automatic collections of real-time data from sensor devices with heterogeneous quality and sensitivity lead to extensive raw data storage. Subsequently, researchers must ensure that the devices are calibrated and ensure that the data are trustworthy, readable, and meaningful to the context. To make research feasible, research institutions – which can also be referred to as research infrastructures – sometimes are dependent on receiving funding from governing institutions such as ESFRI and the Research Council of Norway. In order to receive funding – and with an increased focus on open data sharing between research infrastructures, researchers must adapt to the governments' guidelines and requirements to document their research, influencing their data governance activities. This research aims to contribute empirical insights into the use of intelligent technologies at research infrastructures for environmental monitoring and how researchers' work is affected by the increased use of technology in monitoring. Additionally, researchers' experience adapting to guidelines and requirements on data documenting is also investigated. It is conducted a case study of selected research infrastructures for environmental research in Norway. The study is based on qualitative data collected from structured and semi-structured interviews and relevant documents from governing institutions such as strategy documents, guidelines, and roadmaps. The findings are based on information retrieved from interviews of data managers, environmental researchers, research coordinators, and research managers that daily work at research infrastructures for environmental monitoring. The findings show that IoT-based environmental monitoring is enabled by data governance with the established processes to translate raw, often big data sets, into reliable, readable, and meaningful information to support future reuse and interpretation. The processes are affected by policies, procedures, and standards on collecting and managing the data that consequently affect researchers’ work practices. However, due to constraints in time, funding, and resources, the findings also show that it can be challenging to have the desired quality in researchers’ scientific work.

Industirer I dag blir møtt av et fort marked for digitale tjenester tilbudt av IT selskaper, og gjennom den digitale æra utvalget av tjenester har økt som følger av konstant innovasjon. Men ettersom den integrerte teknologien blir mer avansert, så gjør også kompleksiteten i de utviklede infrastrukturene for informasjon. Målet med denne avhandlingen er å undersøke outsourcing av tjenester som fenomen og skape rik innsikt i den praktiske utviklingen av infrastrukturer for informasjon. Dette blir gjort ved en sosioteknisk tilnærming, ved undersøkelse av tekniske og sosiale faktorer, og deres interaksjoner, i det beskrevede fenomenet. For å bidra med denne kunnskapen en case studie har blitt gjennomført for å undersøke prosesser, elementer, aktører, interaksjoner og utfordringer som tar plass gjennom outsourcing av tjenester, tilbudt av et av de globalt ledende IT selskapene. Gjennom semi-strukturerte intervjuer og en stegvis-deduktiv induserende metode for data analyse, konsepter har blitt manet frem, karakterisert og validert i litteratur fra forskningsområdet for informasjonssystemer i tillegg til gjennom diskusjon med informantene. Disse karakteristikkene har videre blitt modellert og som resultat blitt til et rammeverk for outsourcing a v tjenester som illustrerer kompleksiteten av fenomenet. Resultatene indikerer at de identifiserte faktorene for kompleksitet er gjensidig avhengige og paradoksale. Men en potensiell mulig løsning, en minimum data modell for brukbarhet har dukket opp og blir presentert som motivasjon for videre forskning. Industries today are faced with a large market of digital services offered by IT corporations, and through the digital age the array of services has increased though constant innovation. However, with the integrated technologies advancing the complexity of the information infrastructures developed increases. The aim of this thesis is to investigate the phenomenon of digital service outsourcing in order to create new insight into the practical development of Information Infrastructures. This is done by adapting a sociotechnical approach, studying the technical and social factors, as well as their interactions, in the described phenomenon. In order to provide this knowledge a case study has been conducted, investigating the processes, elements, actors, interactions and challenges occurring though service outsourcing delivered by an IT corporation among the global leaders in the market. Through semi-structured interviews and a stepwise-deductive inductive data analysis emerging concepts have been characterized and further validated in Information System literature and though discussion with the informants. These characteristics have been modeled, resulting in a service outsourcing framework, illustrating the complexity of the phenomenon. Further the results indicate that the complex factors identified are interdependent and paradoxical. However, an emerging potential solution of a minimum viable data model has also been identified and is presented as motivation for further research.