5,997 research outputs found
Information actors beyond modernity and coloniality in times of climate change:A comparative design ethnography on the making of monitors for sustainable futures in Curaçao and Amsterdam, between 2019-2022
In his dissertation, Mr. Goilo developed a cutting-edge theoretical framework for an Anthropology of Information. This study compares information in the context of modernity in Amsterdam and coloniality in Curaçao through the making process of monitors and develops five ways to understand how information can act towards sustainable futures. The research also discusses how the two contexts, that is modernity and coloniality, have been in informational symbiosis for centuries which is producing negative informational side effects within the age of the Anthropocene. By exploring the modernity-coloniality symbiosis of information, the author explains how scholars, policymakers, and data-analysts can act through historical and structural roots of contemporary global inequities related to the production and distribution of information. Ultimately, the five theses propose conditions towards the collective production of knowledge towards a more sustainable planet
Self-supervised learning for transferable representations
Machine learning has undeniably achieved remarkable advances thanks to large labelled datasets and supervised learning. However, this progress is constrained by the labour-intensive annotation process. It is not feasible to generate extensive labelled datasets for every problem we aim to address. Consequently, there has been a notable shift in recent times toward approaches that solely leverage raw data. Among these, self-supervised learning has emerged as a particularly powerful approach, offering scalability to massive datasets and showcasing considerable potential for effective knowledge transfer. This thesis investigates self-supervised representation learning with a strong focus on computer vision applications. We provide a comprehensive survey of self-supervised methods across various modalities, introducing a taxonomy that categorises them into four distinct families while also highlighting practical considerations for real-world implementation. Our focus thenceforth is on the computer vision modality, where we perform a comprehensive benchmark evaluation of state-of-the-art self supervised models against many diverse downstream transfer tasks. Our findings reveal that self-supervised models often outperform supervised learning across a spectrum of tasks, albeit with correlations weakening as tasks transition beyond classification, particularly for datasets with distribution shifts. Digging deeper, we investigate the influence of data augmentation on the transferability of contrastive learners, uncovering a trade-off between spatial and appearance-based invariances that generalise to real-world transformations. This begins to explain the differing empirical performances achieved by self-supervised learners on different downstream tasks, and it showcases the advantages of specialised representations produced with tailored augmentation. Finally, we introduce a novel self-supervised pre-training algorithm for object detection, aligning pre-training with downstream architecture and objectives, leading to reduced localisation errors and improved label efficiency. In conclusion, this thesis contributes a comprehensive understanding of self-supervised representation learning and its role in enabling effective transfer across computer vision tasks
Communicating a Pandemic
This edited volume compares experiences of how the Covid-19 pandemic was communicated in the Nordic countries – Denmark, Finland, Iceland, Norway, and Sweden. The Nordic countries are often discussed in terms of similarities concerning an extensive welfare system, economic policies, media systems, and high levels of trust in societal actors. However, in the wake of a global pandemic, the countries’ coping strategies varied, creating certain question marks on the existence of a “Nordic model”.
The chapters give a broad overview of crisis communication in the Nordic countries during the first year of the Covid-19 pandemic by combining organisational and societal theoretical perspectives and encompassing crisis response from governments, public health authorities, lobbyists, corporations, news media, and citizens. The results show several similarities, such as political and governmental responses highlighting solidarity and the need for exceptional measures, as expressed in press conferences, social media posts, information campaigns, and speeches. The media coverage relied on experts and was mainly informative, with few critical investigations during the initial phases. Moreover, surveys and interviews show the importance of news media for citizens’ coping strategies, but also that citizens mostly trusted both politicians and health authorities during the crisis.
This book is of interest to all who are looking to understand societal crisis management on a comprehensive level. The volume contains chapters from leading experts from all the Nordic countries and is edited by a team with complementary expertise on crisis communication, political communication, and journalism, consisting of Bengt Johansson, Øyvind Ihlen, Jenny Lindholm, and Mark Blach-Ørsten. Publishe
Digital Innovations for a Circular Plastic Economy in Africa
Plastic pollution is one of the biggest challenges of the twenty-first century that requires innovative and varied solutions. Focusing on sub-Saharan Africa, this book brings together interdisciplinary, multi-sectoral and multi-stakeholder perspectives exploring challenges and opportunities for utilising digital innovations to manage and accelerate the transition to a circular plastic economy (CPE).
This book is organised into three sections bringing together discussion of environmental conditions, operational dimensions and country case studies of digital transformation towards the circular plastic economy. It explores the environment for digitisation in the circular economy, bringing together perspectives from practitioners in academia, innovation, policy, civil society and government agencies. The book also highlights specific country case studies in relation to the development and implementation of different innovative ideas to drive the circular plastic economy across the three sub-Saharan African regions. Finally, the book interrogates the policy dimensions and practitioner perspectives towards a digitally enabled circular plastic economy.
Written for a wide range of readers across academia, policy and practice, including researchers, students, small and medium enterprises (SMEs), digital entrepreneurs, non-governmental organisations (NGOs) and multilateral agencies, policymakers and public officials, this book offers unique insights into complex, multilayered issues relating to the production and management of plastic waste and highlights how digital innovations can drive the transition to the circular plastic economy in Africa.
The Open Access version of this book, available at https://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license
Rethink Digital Health Innovation: Understanding Socio-Technical Interoperability as Guiding Concept
Diese Dissertation sucht nach einem theoretischem Grundgerüst, um komplexe, digitale Gesundheitsinnovationen so zu entwickeln, dass sie bessere Erfolgsaussichten haben, auch in der alltäglichen Versorgungspraxis anzukommen. Denn obwohl es weder am Bedarf von noch an Ideen für digitale Gesundheitsinnovationen mangelt, bleibt die Flut an erfolgreich in der Praxis etablierten Lösungen leider aus. Dieser unzureichende Diffusionserfolg einer entwickelten Lösung - gern auch als Pilotitis pathologisiert - offenbart sich insbesondere dann, wenn die geplante Innovation mit größeren Ambitionen und Komplexität verbunden ist. Dem geübten Kritiker werden sofort ketzerische Gegenfragen in den Sinn kommen. Beispielsweise was denn unter komplexen, digitalen Gesundheitsinnovationen verstanden werden soll und ob es überhaupt möglich ist, eine universale Lösungsformel zu finden, die eine erfolgreiche Diffusion digitaler Gesundheitsinnovationen garantieren kann. Beide Fragen sind nicht nur berechtigt, sondern münden letztlich auch in zwei Forschungsstränge, welchen ich mich in dieser Dissertation explizit widme.
In einem ersten Block erarbeite ich eine Abgrenzung jener digitalen Gesundheitsinnovationen, welche derzeit in Literatur und Praxis besondere Aufmerksamkeit aufgrund ihres hohen Potentials zur Versorgungsverbesserung und ihrer resultierenden Komplexität gewidmet ist. Genauer gesagt untersuche ich dominante Zielstellungen und welche Herausforderung mit ihnen einhergehen. Innerhalb der Arbeiten in diesem Forschungsstrang kristallisieren sich vier Zielstellungen heraus: 1. die Unterstützung kontinuierlicher, gemeinschaftlicher Versorgungsprozesse über diverse Leistungserbringer (auch als inter-organisationale Versorgungspfade bekannt); 2. die aktive Einbeziehung der Patient:innen in ihre Versorgungsprozesse (auch als Patient Empowerment oder Patient Engagement bekannt); 3. die Stärkung der sektoren-übergreifenden Zusammenarbeit zwischen Wissenschaft und Versorgungpraxis bis hin zu lernenden Gesundheitssystemen und 4. die Etablierung daten-zentrierter Wertschöpfung für das Gesundheitswesen aufgrund steigender bzgl. Verfügbarkeit valider Daten, neuen Verarbeitungsmethoden (Stichwort Künstliche Intelligenz) sowie den zahlreichen Nutzungsmöglichkeiten. Im Fokus dieser Dissertation stehen daher weniger die autarken, klar abgrenzbaren Innovationen (bspw. eine Symptomtagebuch-App zur Beschwerdedokumentation). Vielmehr adressiert diese Doktorarbeit jene Innovationsvorhaben, welche eine oder mehrere der o.g. Zielstellung verfolgen, ein weiteres technologisches Puzzleteil in komplexe Informationssystemlandschaften hinzufügen und somit im Zusammenspiel mit diversen weiteren IT-Systemen zur Verbesserung der Gesundheitsversorgung und/ oder ihrer Organisation beitragen.
In der Auseinandersetzung mit diesen Zielstellungen und verbundenen Herausforderungen der Systementwicklung rückte das Problem fragmentierter IT-Systemlandschaften des Gesundheitswesens in den Mittelpunkt. Darunter wird der unerfreuliche Zustand verstanden, dass unterschiedliche Informations- und Anwendungssysteme nicht wie gewünscht miteinander interagieren können. So kommt es zu Unterbrechungen von Informationsflüssen und Versorgungsprozessen, welche anderweitig durch fehleranfällige Zusatzaufwände (bspw. Doppeldokumentation) aufgefangen werden müssen. Um diesen Einschränkungen der Effektivität und Effizienz zu begegnen, müssen eben jene IT-System-Silos abgebaut werden. Alle o.g. Zielstellungen ordnen sich dieser defragmentierenden Wirkung unter, in dem sie 1. verschiedene Leistungserbringer, 2. Versorgungsteams und Patient:innen, 3. Wissenschaft und Versorgung oder 4. diverse Datenquellen und moderne Auswertungstechnologien zusammenführen wollen. Doch nun kommt es zu einem komplexen Ringschluss. Einerseits suchen die in dieser Arbeit thematisierten digitalen Gesundheitsinnovationen Wege zur Defragmentierung der Informationssystemlandschaften.
Andererseits ist ihre eingeschränkte Erfolgsquote u.a. in eben jener bestehenden Fragmentierung begründet, die sie aufzulösen suchen.
Mit diesem Erkenntnisgewinn eröffnet sich der zweite Forschungsstrang dieser Arbeit, der sich mit der Eigenschaft der 'Interoperabilität' intensiv auseinandersetzt. Er untersucht, wie diese Eigenschaft eine zentrale Rolle für Innovationsvorhaben in der Digital Health Domäne einnehmen soll. Denn Interoperabilität beschreibt, vereinfacht ausgedrückt, die Fähigkeit von zwei oder mehreren Systemen miteinander gemeinsame Aufgaben zu erfüllen. Sie repräsentiert somit das Kernanliegen der identifizierten Zielstellungen und ist Dreh- und Angelpunkt, wenn eine entwickelte Lösung in eine konkrete Zielumgebung integriert werden soll. Von einem technisch-dominierten Blickwinkel aus betrachtet, geht es hierbei um die Gewährleistung von validen, performanten und sicheren Kommunikationsszenarien, sodass die o.g. Informationsflussbrüche zwischen technischen Teilsystemen abgebaut werden. Ein rein technisches Interoperabilitätsverständnis genügt jedoch nicht, um die Vielfalt an Diffusionsbarrieren von digitalen Gesundheitsinnovationen zu umfassen. Denn beispielsweise das Fehlen adäquater Vergütungsoptionen innerhalb der gesetzlichen Rahmenbedingungen oder eine mangelhafte Passfähigkeit für den bestimmten Versorgungsprozess sind keine rein technischen Probleme. Vielmehr kommt hier eine Grundhaltung der Wirtschaftsinformatik zum Tragen, die Informationssysteme - auch die des Gesundheitswesens - als sozio-technische Systeme begreift und dabei Technologie stets im Zusammenhang mit Menschen, die sie nutzen, von ihr beeinflusst werden oder sie organisieren, betrachtet. Soll eine digitale Gesundheitsinnovation, die einen Mehrwert gemäß der o.g. Zielstellungen verspricht, in eine existierende Informationssystemlandschaft der Gesundheitsversorgung integriert werden, so muss sie aus technischen sowie nicht-technischen Gesichtspunkten 'interoperabel' sein.
Zwar ist die Notwendigkeit von Interoperabilität in der Wissenschaft, Politik und Praxis bekannt und auch positive Bewegungen der Domäne hin zu mehr Interoperabilität sind zu verspüren. Jedoch dominiert dabei einerseits ein technisches Verständnis und andererseits bleibt das Potential dieser Eigenschaft als Leitmotiv für das Innovationsmanagement bislang weitestgehend ungenutzt. An genau dieser Stelle knüpft nun der Hauptbeitrag dieser Doktorarbeit an, in dem sie eine sozio-technische Konzeptualisierung und Kontextualisierung von Interoperabilität für künftige digitale Gesundheitsinnovationen vorschlägt. Literatur- und expertenbasiert wird ein Rahmenwerk erarbeitet - das Digital Health Innovation Interoperability Framework - das insbesondere Innovatoren und Innovationsfördernde dabei unterstützen soll, die Diffusionswahrscheinlichkeit in die Praxis zu erhöhen. Nun sind mit diesem Framework viele Erkenntnisse und Botschaften verbunden, die ich für diesen Prolog wie folgt zusammenfassen möchte:
1. Um die Entwicklung digitaler Gesundheitsinnovationen bestmöglich auf eine erfolgreiche
Integration in eine bestimmte Zielumgebung auszurichten, sind die Realisierung
eines neuartigen Wertversprechens sowie die Gewährleistung sozio-technischer Interoperabilität
die zwei zusammenhängenden Hauptaufgaben eines Innovationsprozesses.
2. Die Gewährleistung von Interoperabilität ist eine aktiv zu verantwortende Managementaufgabe
und wird durch projektspezifische Bedingungen sowie von externen und internen Dynamiken beeinflusst.
3. Sozio-technische Interoperabilität im Kontext digitaler Gesundheitsinnovationen kann
über sieben, interdependente Ebenen definiert werden: Politische und regulatorische Bedingungen;
Vertragsbedingungen; Versorgungs- und Geschäftsprozesse; Nutzung; Information; Anwendungen; IT-Infrastruktur.
4. Um Interoperabilität auf jeder dieser Ebenen zu gewährleisten, sind Strategien differenziert
zu definieren, welche auf einem Kontinuum zwischen Kompatibilitätsanforderungen
aufseiten der Innovation und der Motivation von Anpassungen aufseiten der Zielumgebung
verortet werden können.
5. Das Streben nach mehr Interoperabilität fördert sowohl den nachhaltigen Erfolg der einzelnen digitalen
Gesundheitsinnovation als auch die Defragmentierung existierender Informationssystemlandschaften und
trägt somit zur Verbesserung des Gesundheitswesens bei.
Zugegeben: die letzte dieser fünf Botschaften trägt eher die Färbung einer Überzeugung, als dass sie ein Ergebnis wissenschaftlicher Beweisführung ist. Dennoch empfinde ich diese, wenn auch persönliche Erkenntnis als Maxim der Domäne, der ich mich zugehörig fühle - der IT-Systementwicklung des Gesundheitswesens
Archaeological palaeoenvironmental archives: challenges and potential
This Arts and Humanities Research Council (AHRC) sponsored collaborative doctoral project represents one of
the most significant efforts to collate quantitative and qualitative data that can elucidate practices related to
archaeological palaeoenvironmental archiving in England. The research has revealed that archived
palaeoenvironmental remains are valuable resources for archaeological research and can clarify subjects that
include the adoption and importation of exotic species, plant and insect invasion, human health and diet, and
plant and animal husbandry practices. In addition to scientific research, archived palaeoenvironmental remains
can provide evidence-based narratives of human resilience and climate change and offer evidence of the
scientific process, making them ideal resources for public science engagement. These areas of potential have
been realised at an imperative time; given that waterlogged palaeoenvironmental remains at significant sites
such as Star Carr, Must Farm, and Flag Fen, archaeological deposits in towns and cities are at risk of decay due
to climate change-related factors, and unsustainable agricultural practices. Innovative approaches to collecting
and archiving palaeoenvironmental remains and maintaining existing archives will permit the creation of an
accessible and thorough national resource that can service archaeologists and researchers in the related fields
of biology and natural history. Furthermore, a concerted effort to recognise absences in archaeological
archives, matched by an effort to supply these deficiencies, can produce a resource that can contribute to an
enduring geographical and temporal record of England's biodiversity, which can be used in perpetuity in the
face of diminishing archaeological and contemporary natural resources.
To realise these opportunities, particular challenges must be overcome. The most prominent of these include
inconsistent collection policies resulting from pressures associated with shortages in storage capacity and
declining specialist knowledge in museums and repositories combined with variable curation practices. Many of
these challenges can be resolved by developing a dedicated storage facility that can focus on the ongoing
conservation and curation of palaeoenvironmental remains. Combined with an OASIS + module designed to
handle and disseminate data pertaining to palaeoenvironmental archives, remains would be findable,
accessible, and interoperable with biological archives and collections worldwide. Providing a national centre for
curating palaeoenvironmental remains and a dedicated digital repository will require significant funding.
Funding sources could be identified through collaboration with other disciplines. If sufficient funding cannot be
identified, options that would require less financial investment, such as high-level archive audits and the
production of guidance documents, will be able to assist all stakeholders with the improved curation,
management, and promotion of the archived resource
Analysis in Web 3D Environments of Thematic Research Networks on Immersive Learning through Variation of Clustering Criteria
Este projeto tem como objetivo desenvolver uma ferramenta de visualização 3D baseada na web
que proporciona uma compreensão global do campo de Aprendizagem Imersiva. As redes temáti-
cas são uma abordagem bem estabelecida para lidar com esses desafios. Portanto, foi realizada
uma revisão sistemática da literatura para extrair métodos e critérios de clustering em redes
temáticas. A metodologia empregada neste estudo é a pesquisa de Design Science Research,
que envolveu o desenvolvimento e a avaliação iterativos da ferramenta de visualização. Entre-
vistas com especialistas foram realizadas para identificar os requisitos, e métodos rigorosos, in-
cluindo gravação, análise e transcrição das entrevistas, foram aplicados para verificar a relevância
da pesquisa. A ferramenta utiliza uma abordagem de visualização de node-link para visualizar
estratégias, práticas e artigos associados à aprendizagem imersiva. Além disso, oferece uma var-
iedade de funcionalidades de filtragem, permitindo que os usuários filtrem por estratégias, práticas,
autores, instituições e outros. Além disso, a ferramenta incorpora várias funcionalidades de clus-
tering, como detecção de comunidades usando o algoritmo de Louvain, com variação de critérios
de clustering , como associação de temas e de artigos, citação de artigos, co-citação e outros.
Os usuários também podem controlar a estrutura da rede modificando o tamanho das clustering,
o número e as cores das comunidades. A ferramenta apresenta métodos exploratórios de redes
temáticas para navegar no ambiente. Ao combinar redes temáticas com capacidades de clustering
e filtragem, essa ferramenta tem como objetivo fornecer uma compreensão global do campo cien-
tífico. Sua integração única de tecnologias Web e 3D, juntamente com métodos exploratórios, a
diferencia das ferramentas de visualização existentes. Os poderosos algoritmos de clustering da
ferramenta, oferecendo critérios diversos para entender as relações conceituais, têm o potencial de
ter um impacto significativo na comunidade de aprendizagem imersiva. Ela é projetada para servir
como um artefato inovador que aprimora as capacidades analíticas de pesquisadores, educadores
e estudantes na área.This project aims to develop a Web-based 3D visualization tool that provides a global understanding of the field of Immersive Learning. Thematic networks are a well-established approach for addressing such challenges. Therefore, a systematic literature review was conducted to extract clustering methods and criteria in thematic networks. The methodology employed in this study is Design Science research, which involved iterative development and evaluation of the visualization
tool. Expert interviews were conducted to identify requirements, and rigorous methods, including recording, analyzing, and transcribing interviews, were applied to ascertain the research's
relevance. The tool utilizes a node-link visualization approach to represent immersive learning
strategies, practices, and associated papers. Additionally, it offers a range of filtering functionali-
ties, allowing users to filter by strategies, practices, authors, institutions, and more. Furthermore,
the tool incorporates various clustering functionalities, such as community detection using the
Louvain Algorithm, with variable clustering criteria such as theme and paper association, paper
citation, co-citation, and others. Users can also control the network's structure by modifying clus-
ter size, number, and community colors. The tool features thematic networks exploratory methods
for navigating the environment. By combining thematic networks with clustering and filtering
capabilities, this tool aims to provide a global understanding of the scientific field. Its unique
integration of Web and 3D technologies, along with exploratory methods, distinguishes it from
existing visualization tools. The tool's powerful clustering algorithms, offering diverse criteria
for understanding concept relationships, have the potential to make a significant impact in the immersive learning community. It is designed to serve as an innovative artifact that enhances the
analytical capabilities of researchers, educators, and students in the field
Image-based Decision Support Systems: Technical Concepts, Design Knowledge, and Applications for Sustainability
Unstructured data accounts for 80-90% of all data generated, with image data contributing its largest portion. In recent years, the field of computer vision, fueled by deep learning techniques, has made significant advances in exploiting this data to generate value. However, often computer vision models are not sufficient for value creation. In these cases, image-based decision support systems (IB-DSSs), i.e., decision support systems that rely on images and computer vision, can be used to create value by combining human and artificial intelligence. Despite its potential, there is only little work on IB-DSSs so far.
In this thesis, we develop technical foundations and design knowledge for IBDSSs and demonstrate the possible positive effect of IB-DSSs on environmental sustainability. The theoretical contributions of this work are based on and evaluated in a series of artifacts in practical use cases: First, we use technical experiments to demonstrate the feasibility of innovative approaches to exploit images for IBDSSs.
We show the feasibility of deep-learning-based computer vision and identify future research opportunities based on one of our practical use cases. Building on this, we develop and evaluate a novel approach for combining human and artificial intelligence for value creation from image data. Second, we develop design knowledge that can serve as a blueprint for future IB-DSSs. We perform two design science research studies to formulate generalizable principles for purposeful design — one for IB-DSSs and one for the subclass of image-mining-based decision support systems (IM-DSSs). While IB-DSSs can provide decision support based on single images, IM-DSSs are suitable when large amounts of image data are available and required for decision-making. Third, we demonstrate the viability of applying IBDSSs to enhance environmental sustainability by performing life cycle assessments for two practical use cases — one in which the IB-DSS enables a prolonged product lifetime and one in which the IB-DSS facilitates an improvement of manufacturing processes.
We hope this thesis will contribute to expand the use and effectiveness of imagebased decision support systems in practice and will provide directions for future research
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