Denna rapports frågeställning är: hur lämpar sig psykiatrins data för en datalagerstruktur och inleds med en bakgrund där en litteraturstudie genomförs. Efter detta kommer en metod del och en genomförande del där intervjuer med avdelningschefer, verksamhetschefen, samt en verksamhetsutvecklare på ett svenskt universitetssjukhus psykiatriavdelning beskrivs. Genom observationer och analys av sjukhusets data samt svaren från respondenterna sammanställdes ett resultat som visar emot att detta sjukhus inte har en god grund för en datalagerstruktur, men genom omprioriteringar kan detta förbättras. Resultatet baserades på forskning gjord av Inmon (2005) och fyra av de kategorier som han anser är mest relevanta för en datalagerstruktur, samt insamlad data från universitetssjukhuset. Det framkom även att alla svenska sjukhus verkar ha problem med sina system och att hela svenska vården är i en uppgraderingsfas där det vid en sådan investering bör prioriteras att skapa fungerande datalagerstrukturer för att kunna analysera vilka resultat vården ger. Just nu fattas beslut i blindo och detta kommer inte förändras om inte förändring sker. / This report's question is: how does psychiatry's data fit into a data warehouse structure and starts with a background in which a literature study is carried out. After this, a method part and an implementation part will be described in which interviews with department heads, the operations manager, as well as an operations developer at a Swedish university hospital's psychiatry department are described. Through observations and analysis of the hospital data and the responses of the respondents, a result was compiled which shows that this hospital does not have a good basis for a data warehouse structure, but through re-prioritization this can be improved. The result was based on research done by Inmon (2005) and four of the categories that he considers to be most relevant to a data warehouse structure, as well as data collected from the university hospital. It also emerged that all Swedish hospitals seem to have problems with their systems and that the entire Swedish healthcare system is in an upgrade phase where it should be prioritized in such an investment to create functioning data warehouse structures in order to be able to analyze the results the health care gives. Right now, decisions are being made blindly and this will not change unless change is made.

Recent innovations in the information technology and computing devices magnified the volume of available information. Today’s decision makers face the challenge of analyzing ever more data in shorter timeframes. Demand for technology that can efficiently assist systematic data analysis is constantly growing. Development of dedicated information systems is, however, difficult both from organizational and technological point of view. First, traditional software production is a complex and time-consuming process that can not be performed under time-pressure. Second, changing business conditions and evolving stakeholder needs require solutions that can be efficiently tailored over time. Finally, costs of custom software development are high, so that not all use cases and scenarios can be covered sufficiently. This thesis proposes a holistic approach to address the challenges above and to enable efficient development of decision support software. The main idea is to empower end users, i.e., decision makers, in constructing their own case-specific solutions. The proposed approach called Web-Composition for End-User Development consists of a systematic process for development and evolution of decision support systems, assistance mechanisms to address lack of programming skills by decision makers and evolution facilities to enable cost- and time-efficient extensibility of user-produced solutions. The thesis describes implementation of the devised principles and ideas in the context of several open-source projects and application scenarios. Applicability and usability of the concepts are demonstrated in user studies with respective target groups. Based on the outcome analysis the thesis concludes that end users can and should actively participate in construction of decision support software.

Sjukvården visar intresse för användning av Artificiell Intelligens (AI) och inom behandling för psykisk ohälsa finns behov för stöd. Intelligenta beslutsstöd kan bidra till minskad belastning för vårdpersonal och bättre behandling för patienter, men sjukvårdens känsliga natur och de konsekvenser som kan uppstå vid försummelse medför etiska utmaningar. Behandling av psykisk ohälsa är komplext och behöver utforskas för att identifiera de potentiella etiska utmaningar som kan uppstå. Genom en kvalitativ intervjustudie med åtta deltagare har området utforskats både bland AI-forskare och vårdpersonal, där insikter från båda kontexter har analyserats för att identifiera och utforska återkommande etiska utmaningar. Genom insamlad empiri och litteraturstudie har fem etiska utmaningar identifierats och utforskats: hantera felaktiga rekommendationer, hantera moraliska dilemman, uppnå patientautonomi, ansvarsdilemmat, och skapa förtroende. / Health care has taken interest in the use of AI (Artificial Intelligence) and mental health services are in need of support. Intelligent decision support systems can contribute to reduced workload for health care professionals and better treatment for patients, but the sensitive nature of health care and the possible consequences in the event of neglect or malpractice pose ethical challenges. Treatment of mental illness is complex and needs to be explored in order to identify the potential ethical challenges that can arise. Through an interview study consisting of eight participants, the problem area has been explored amongst both AI researchers and health care professionals, where insights from both contexts have been analysed in order to identify and explore recurring ethical challenges. Through empirical data and a literature study, five ethical challenges have been identified and explored: handle incorrect recommendations, handle moral dilemmas, achieve patient autonomy, the liability dilemma, and generate trust.

Data marts and caching are two closely related concepts in the domain of multi-dimensional data. Both store pre-computed data to provide fast response times for complex OLAP queries, and for both it must be guaranteed that every query can be completely processed. However, they differ extremely in their update behaviour which we utilise to build a specific data mart extended by cache semantics. In this paper, we introduce a novel cache exploitation concept for data marts - coarse-grained caching - in which the containedness check for a multi-dimensional query is done through the comparison of the expected and the actual cardinalities. Therefore, we subdivide the multi-dimensional data into coarse partitions, the so called cubletets, which allow to specify the completeness criteria for incoming queries. We show that during query processing, the completeness check is done with no additional costs.

Business simulation games are used in educational institutions and various industries in the private and public sector to train students and employees to practice the principles of management and decision-making skills by providing a fail-safe environment and enabling them to reflect on their simulation results. These games are generally advanced multiuser environments where a user, or a group of users, have access to a virtual company for making business decisions. Some of these games are expensive and their licences are time limited; typically, such a licence is only valid during the duration of the course. In general, these games are not available for the public as part of informal instructional courses. In Canada, teaching informal courses to immigrants and refugees, which involve data-driven decision making, to prepare them for future challenges they might encounter as business owners, can be challenging; especially considering language barriers and non-business-related backgrounds obtained outside of Canada. Furthermore, based on their decision-making styles, cognitive limitations, and past experiences, people may have an inaccurate perception of the problem or challenge they face, this could lead to poor decision making of the team they are part of and, therefore, this could reflect in the effectiveness of an organization as a whole. The objective of this research is to enrich current teaching tools in decision-making processes in entrepreneurship courses for newcomers in Canada with a comprehensive and visual representation of operational business problems involved in Business Intelligence and data analytics. More specifically, we designed and developed a 3D Business Simulation Game with randomized scenarios using modern technologies, such as Unreal Engine as the game engine; Adobe Fuse for the character creation, Mixamo for animation of the character, and Substance Painter for textures and materials for the assets. The research was conducted with the participation of the students of the Business Creation and Project Management course at VIRCS (Victoria Immigrant and Refugee Centre Society) where we tested this game on each one of the five units of the course. After designing, developing, and testing the 3D business simulation game, we conducted a comprehensive evaluation to investigate whether the decisions students made while playing were correct or not. We also evaluated whether they felt that the challenges were easier to understand, both as a team and individually, when they used the 3D business simulation game compared to only the written description of the problems. The main results we obtained from our study are the following: After playing the business simulation game, students became more aware of the importance of making correct decisions in different business scenarios. They made sure that the whole team understood the problem, and they felt generally good about their understanding of the course content. We also noticed that when the animation was not part of the business simulation game, they seemed to be confused when following written instructions. This indicate that they depended on the animations for their decision-making. We believe that, in some ways, the course and the 3D business simulation game we created for this research were a great opportunity to observe students becoming more confident in their future in Canada as entrepreneurs. We observed that, once the game has been used, the students become more participatory in class, the discussion of the course material increases, and in general, the students seem to enjoy the course more. / Graduate

Die vorliegende Arbeit beschreibt ein wissensbasiertes Decision Support System (DSS) zur Analyse von Wirkungsbeziehungen in einem betriebswirtschaftlichen Umfeld, um die Ursachen von beobachteten Wirkungen zu verstehen und dadurch eine Unterstützung in Entscheidungssituationen zu ermöglichen. Die Umweltbedingungen einer Entscheidungssituation werden während der Analyse berücksichtigt, sodass die Unterstützung auf die jeweilige Situation angepasst ist. Den Kern des Konzeptes stellen eine Wissensbasis sowie eine Ablaufsteuerung zur situativen Auswertung der Wissensbasis dar. Die Wissensbasis speichert Wirkungsbeziehungen zwischen Elementen in Form eines semantischen Netzes. Ein Element besitzt zudem Metainformationen über interne und externe, beliebig strukturierte Daten zur situativen Validierung der Wirkungsbeziehungen. Ebenfalls können Zeitverzögerungen bei Wirkungsbeziehungen berücksichtigt werden. Die Ablaufsteuerung verarbeitet das gespeicherte Wissen aus der Wissensbasis zur situativen Entscheidungsunterstützung in drei aufeinander aufbauenden Phasen. Die Initialisierungsphase dient der Eingabe einer Entscheidungssituation ins System sowie dem Matching der Entscheidungssituation mit Elementen der Wissensbasis. Die Explorationsphase durchsucht die Wissensbasis anhand der Wirkungsbeziehungen nach potenziell relevanten Elementen für die Entscheidungssituation und validiert diese mit statistischen Methoden, indem die Daten der potenziell relevanten Elemente anhand der Metainformationen abgerufen und mit geeigneten Methoden ausgewertet werden. Die Evaluationsphase ermöglicht es dem Anwender, die Ergebnisse zu überprüfen und optional die Wissensbasis anzupassen. Zur Evaluation des Konzeptes erfolgt eine prototypische Implementierung sowie deren empirische Evaluation mit einem Laborexperiment. Auf Basis des Aufgabe-Technologie-Fit-Modells wird eine bessere Eignung des Prototyps im Vergleich zu einer am Markt etablierten DSS-Software ohne automatisierte Analysen von Wirkungsbeziehungen nachgewiesen.

As climate change is becoming an increasingly more alarming threat in society, sustainability as a topic becomes more and more important in relation to a range of business activities, software development being one. Several frameworks for how software development and computing products should be developed and evaluated on the basis of sustainability and climate impact are being developed, but there are no standardized ways to go about this type of work and the topic is still under prioritized in favor of other non functional requirements, like financial aspects. Models for how the climate impact of different parts of the process chain can be estimated are being implemented into the operations of many major companies and goals surrounding reduced emissions are being set. However, these goals are not being translated into the day-to-day operations of developers and other stakeholders developing these digital products. This thesis is centered around a qualitative study that investigates the attitudes of software developers and product owners at the Swedish public service broadcasting company SVT in regards to working with sustainability. The challenges they face in relation to reducing the climate impact of their digital platforms in general, and their streaming platforms in particular, are presented and a stakeholder co-created tool to meet these challenges was prototyped. / I takt med att klimatförändringarna blir ett allt mer alarmerande hot i samhället blir hållbarhet som ämne allt viktigare i förhållande till en rad olika verksamheter, där mjukvaruutveckling är en. Åtskilliga ramverk för hur mjukvaruutveckling och digitala produkter ska utvecklas och utvärderas utifrån hållbarhet och klimatpåverkan är under utveckling, men det finns inga standardiseringar för utförandet av den här typen av arbete och ämnet är fortfarande underprioriterat till förmån för andra icke-funktionella krav, som till exempel finansiella aspekter. Modeller för hur klimatpåverkan från olika delar av processkedjan kan estimeras blir implementerade i många större företags verksamheter och mål kring minskade utsläpp sätts upp. Dessa mål översätts dock inte till den dagliga verksamheten för utvecklare och andra delaktiga medarbetare som utvecklar dessa digitala produkter. Denna studie är centrerad kring en kvalitativ undersökning som kartlägger inställningarna och attityderna till att arbeta med hållbarhet hos mjukvaruutvecklare och produktägare på SVT. De utmaningar de står inför när det gäller att minska klimatpåverkan från deras digitala plattformar i allmänhet, och deras streamingplattformar i synnerhet, presenteras och ett samskapat verktyg för att möta dessa utmaningar togs fram som prototyp.

This pilot study has the twofold purpose of analyzing the effect of XAI explanations on the mental models of economic games participants, and testing the feasibility of the methodology devised for it. To achieve this, we compared the contribution behavior and mental models of 30 participants playing a public good game. Playing in pairs, a total of 10 participants played in each of three different conditions: i) a condition with a decision support system providing suggestions for contributions; ii) a condition with the decision support system and explanations for its suggestions; iii) a control condition. Upon finishing the game, all participants completed a Retrospection Task questionnaire to elicit their mental models about the game’s goals and partner’s behavior. Our results showed differences in the contribution behavior and mental models of the participants between the three conditions, with the condition with explanations presenting consistently higher contributions and participants reporting prosocial attitudes. Through these findings, this pilot study demonstrates the feasibility of the methodology and argues for the need of a larger-scale study to further investigate the effect of XAI explanations on the users’ mental models. / Denna pilotstudie har det dubbla syftet att analysera effekten av XAI-förklaringar på de mentala representationerna hos deltagarna i ekonomiska spel och att testa genomförbarheten av den metod som utarbetats för studien. För att uppnå detta jämförde vi bidragsbeteendet och de mentala representationerna hos 30 deltagare som spelade ett spel om kollektiva nyttigheter. Totalt 10 deltagare spelade parvis i var och en av tre olika behandlingar: i) en med ett beslutsstödsystem som ger förslag på bidrag, ii) en med beslutsstödsystemet och förklaringar till dess förslag, iii) en kontrollgrupp. Efter att ha avslutat spelet fyllde alla deltagare i ett frågeformulär om en retrospektionsuppgift för att utvärdera deras mentala representationer om spelets mål och partnerns beteende. Våra resultat visade skillnader i deltagarnas bidragsbeteende och mentala modeller mellan de tre behandlingarna, där behandlingen med förklaringar presenterade genomgående högre bidrag och deltagare som rapporterade prosociala attityder. Genom dessa resultat visar den här pilotstudien att metoden är genomförbar och argumenterar för behovet av en studie i större skala för att ytterligare undersöka effekten av XAI-förklaringar på användarnas mentala modeller.

Research has focused heavily on the study of Clinical Decision Support Systems. However, CDS systems have generally had little impact on clinical practice. One of the most important reasons is the lack of human-computer interaction (HCI) considerations in designing these systems. Although physicians play an essential role in healthcare decision-making, there is little literature describing physicians' expectations and preferences prior to the development of these systems, which is an essential phase in user-centered design.This study aims to answer the following research question: What do physicians expect of interacting with future clinical decision support systems? An exploratory qualitative study was conducted, and data were collected by interviewing 9 physicians practicing in Sweden. A thematic analysis was used for data analysis, and the findings are four themes: 1) physicians' Expectations related to clinical practice; 2) physicians' expectations related to physician-patient relationship; 3) physicians' expectations related to the physician's role 4) physicians' expectations related to CDS governance.The research findings contribute to the knowledge of Anticipated UX in the context of healthcare and CDS systems. The empirical findings on potential user expectations are valuable for understanding the diversity of user experience and user expectations as phenomena in the specific domain of CDS systems. Service designers can utilize and build on the empirical findings to develop positive user experiences of future CDS systems

Un sistema de gestión de sequías apropiado requiere de la anticipación de los posibles efectos que un episodio de este tipo tenga sobre el sistema de recursos hídricos. Esta tarea sin embargo resulta más complicada de lo que parece. En primer lugar, debido al alto grado de incertidumbre existente en la predicción de variables hidrológicas futuras. Y en segundo, debido al riesgo de sobrerreacción en la activación de medidas de mitigación generando falsa sensación de escasez, o sequía artificial. A este respecto, los planes especiales de sequía proveen de herramientas para la gestión eficiente de situaciones con escasez de recursos y la preparación de cara a futuros eventos. De todos modos, las diferentes estrategias de operación seguidas en cada sistema de recursos hídricos hacen que las herramientas que en algunos casos resultaron altamente útiles no lo sean tanto cuando se aplican en sistemas distintos. Debido a la falta de tiempo y/o al exceso de confianza en los trabajos realizados por terceros, con excelentes resultados en sus respectivos casos, a veces se cae en el error de implementar metodologías no del todo apropiadas en sistemas con requisitos completamente distintos. El desarrollo y utilización de metodologías generalizadas aplicables a diferentes sistemas y capaces de proporcionar resultados adaptados a cada caso es, por tanto, muy deseable. Este es el caso de las herramientas de modelación de sistemas de recursos hídricos generalizadas. Estas permiten homogeneizar los procesos mientras siguen siendo los suficientemente adaptables para proporcionar resultados apropiados para cada caso de estudio. Esta tesis presenta una serie de herramientas destinadas a avanzar en el análisis y comprensión de los sistemas de recursos hídricos, haciendo énfasis en la prevención de sequías y la gestión de riesgos. Las herramientas desarrolladas incluyen: un modelo de optimización generalizado para esquemas de recursos hídricos, con capacidad para la representación detallada de cualquier sistema de recursos hídricos, y una metodología de análisis de riesgo basada en la optimización de Monte Carlo con múltiples series sintéticas. Con estas herramientas es posible incluir tanto la componente superficial como la subterránea del sistema estudiado dentro del proceso de optimización. La optimización está basada en la resolución iterativa de redes de flujo. Se probó la consistencia y eficiencia de diferentes algoritmos de resolución para encontrar un balance entre la velocidad de cálculo, el número de iteraciones, y la consistencia de los resultados, aportando recomendaciones para el uso de cada algoritmo dadas las diferencias entre los mismos. Las herramientas desarrolladas se aplican en dos casos de estudio reales en la evaluación y posibilidad de complementación de los sistemas de monitorización y alerta temprana de sequías existentes en los mismos. En el primer caso, se propone un enfoque alternativo para la monitorización de la sequía en el sistema de operación anual del río Órbigo (España), complementándolo con la utilización de la metodología de análisis de riesgo. En el segundo caso, las herramientas se emplean en un sistema con una estrategia de operación completamente distinta. Se estudia como el análisis de riesgo de la gestión óptima puede ayudar a la activación anticipada de los escenarios de sequía en los sistemas de los ríos Júcar y Turia, cuya operación es hiperanual. En esta ocasión, el sistema de indicadores existente goza de una gran confianza por parte de los usuarios. La metodología de análisis de riesgo es, sin embargo, capaz de anticipar los eventos de sequía con mayor alarma, aspecto que es deseable si se quiere evitar que los episodios en desarrollo vayan a más. En ambos casos se muestra como la evaluación anticipada de las posibles situaciones futuras del sistema permiten una definición confiable de los escenarios de sequía con suficiente antelación para la activación efectiva de medidas de prevención y/o mitigación en caso de ser necesarias. La utilización de indicadores provenientes de modelos frente a indicadores basados en datos observados es complementaria y ambos deberían utilizarse de forma conjunta para mejorar la gestión preventiva de los sistemas de recursos hídricos. El empleo de modelos de optimización en situaciones de incertidumbre hidrológica es muy apropiado gracias a la no necesidad de definir reglas de gestión para obtener los mejores resultados del sistema, y teniendo en cuenta que las reglas de operación habituales pueden no ser completamente adecuadas en estas ocasiones. / Haro Monteagudo, D. (2014). Methodology for the optimal management design of water resources system under hydrologic uncertainty [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/45996