Attempts to share information between public sector organisations over time: A case-based exploration of value conflicts

Despite the importance of inter-organisational information sharing (IOIS) in the public sector, such endeavours often fail. Existing research has shown that the values held by collaborating organisations are one important factor affecting these kinds of initiatives. However, research has sought only to a limited extent to address how value conflicts come into play over time. Therefore, this paper aims to explore how conflicting values shape an inter-organisational information-sharing practice in the public sector over time. Using the local/global network framework, we analyse four years’ worth of information sharing in an inter-organisational advisory group in the context of Swedish nuclear waste management. We conclude that different value conflicts are emphasised to different extents at different points in time. That is, values do not uniformly affect IOIS activities, and such conflicts over time reduce the set of potential IOIS activities. We also conclude that when IOIS activities are driven by an individual organisation’s values, individual value rational activities may co-exist with a dysfunctional long-term IOIS practice.publishedVersio

VR-Participation & Dialogue: Towards Integrated Framework for Virtual Reality-Mediated Consensus and Community Building

Successful e-Participation requires a thriving community of users-citizens who engage and collaborate with governments and decision makers on key democratic and social maters. Effective community building and meaningful social interactions are contingent on strong, organic consensus achieved through engaging dialogue rather than discussions or argumentation. The emerging social Virtual Reality platforms offer new means of immersive communication that brings an opportunity to overcome some of the challenges identified to be hindering state-of-the-art e-Participation from supporting constructive citizen-to-government dialogue. In this paper we investigate the key concepts and explore the principles of dialogue and consensus building in the context of e-Participation. We match those principles with specific VR affordances and propose an Integrative Framework for Virtual-Reality-Mediated Consensus and Community Building. Finally, we discuss the application of the framework to e-Participation

Technologies and Social Justice Outcomes in Sex Work Charities: Fighting Stigma, Saving Lives

Sex workers' rights are human rights, and as such are an issue inherently based in social, criminal, and political justice debates. As HCI continues to move towards feminist and social justice oriented research and design approaches, we argue that we need to take into consideration the difficulties faced by sex workers; and explore how technology can and does mediate social justice outcomes for them. We contribute directly to this challenge by providing an empirical account of a charity whose work is built on the underlying move towards social and criminal justice for sex workers in the UK. Through ethnographic fieldwork, meetings, interviews, surveys, and creative workshops we describe the different points of view associated with the charity from a variety of stakeholders. We discuss their service provision and the ways in which HCI is uniquely positioned to be able respond to the needs of and to support sex work support services

Distributed Ledger Technology for the systematic Investigation and Reduction of Information Asymmetry in Collaborative Networks

Costs, risks and inefficiencies in Collaborative Networks (CNs) resulting from information asymmetries have been discussed in the scientific community for years. In this work, supply chain networks, as common representative of CNs, are used as object of investigation. Therein, problems and requirements of interorganizational information exchange are elaborated as well as the potential role Distributed Ledger Technology (DLT) could play to address them. As major challenge, convincing all relevant network partners to resolve asymmetric information by sharing sensitive data is identified. To face this issue, the value of shared information is prioritized as a motivational aspect. Finally, we propose a search process to systematically assess the benefits of information sharing in collaborative networks. To coordinate and implement this process regarding the derived requirements of CNs we propose system components based on DLT design patterns

A Method to Screen, Assess, and Prepare Open Data for Use

Open data's value-creating capabilities and innovation potential are widely recognized, resulting in a notable increase in the number of published open data sources. A crucial challenge for companies intending to leverage open data is to identify suitable open datasets that support specific business scenarios and prepare these datasets for use. Researchers have developed several open data assessment techniques, but those are restricted in scope, do not consider the use context, and are not embedded in the complete set of activities required for open data consumption in enterprises. Therefore, our research aims to develop prescriptive knowledge in the form of a meaningful method to screen, assess, and prepare open data for use in an enterprise setting. Our findings complement existing open data assessment techniques by providing methodological guidance to prepare open data of uncertain quality for use in a value-adding and demand-oriented manner, enabled by knowledge graphs and linked data concepts. From an academic perspective, our research conceptualizes open data preparation as a purposeful and value-creating process

Novel Techniques for Automated Dental Identification

Automated dental identification is one of the best candidates for postmortem identification. With the large number of victims encountered in mass disasters, automating the process of postmortem identification is receiving an increased attention. This dissertation introduces new approaches for different stages of Automated Dental Identification system: These stages include segmentations, classification, labeling, and matching:;We modified the seam carving technique to adapt the problem of segmenting dental image records into individual teeth. We propose a two-stage teeth segmentation approach for segmenting the dental images. In the first stage, the teeth images are preprocessed by a two-step thresholding technique, which starts with an iterative thresholding followed by an adaptive thresholding to binarize the teeth images. In the second stage, we adapt the seam carving technique on the binary images, using both horizontal and vertical seams, to separate each individual tooth. We have obtained an optimality rate of 54.02% for the bitewing type images, which is superior to all existing fully automated dental segmentation algorithms in the literature, and a failure rate of 1.05%. For the periapical type images, we have obtained a high optimality rate of 58.13% and a low failure rate of 0.74 which also surpasses the performance of existing techniques. An important problem in automated dental identification is automatic classification of teeth into four classes (molars, premolars, canines, and incisors). A dental chart is a key to avoiding illogical comparisons that inefficiently consume the limited computational resources, and may mislead decision-making. We tackle this composite problem using a two-stage approach. The first stage, utilizes low computational-cost, appearance-based features, using Orthogonal Locality Preserving Projections (OLPP) for assigning an initial class. The second stage applies a string matching technique, based on teeth neighborhood rules, to validate initial teeth-classes and hence to assign each tooth a number corresponding to its location in the dental chart, even in the presence of a missed tooth. The experimental results of teeth classification show that on a large dataset of bitewing and periapical films, the proposed approach achieves overall classification accuracy of 77% and teeth class validation enhances the overall teeth classification accuracy to 87% which is slightly better than the performance obtained from previous methods based on EigenTeeth the performance of which is 75% and 86%, respectively.;We present a new technique that searches the dental database to find a candidate list. We use dental records of the FBI\u27s Criminal Justice Service (CJIC) ADIS database, that contains 104 records (about 500 bitewing and periapical films) involving more than 2000 teeth, 47 Antemortem (AM) records and 57 Postmortem (PM) records with 20 matched records.;The proposed approach consists of two main stages, the first stage is to preprocess the dental records (segmentation and teeth labeling classification) in order to get a reliable, appearance-based, low computational-cost feature. In the second stage, we developed a technique based on LaplacianTeeth using OLPP algorithm to produce a candidate list. The proposed technique can correctly retrieve the dental records 65% in the 5 top ranks while the method based on EigenTeeth remains at 60%. The proposed approach takes about 0.17 seconds to make record to record comparison while the other method based on EigenTeeth takes about 0.09 seconds.;Finally, we address the teeth matching problem by presenting a new technique for dental record retrieval. The technique is based on the matching of the Scale Invariant feature Transform (SIFT) descriptors guided by the teeth contour between the subject and reference dental records. Our fundamental objective is to accomplish a relatively short match list, with a high probability of having the correct match reference. The proposed technique correctly retrieves the dental records with performance rates of 35% and 75% in the 1 and 5 top ranks respectively, and takes only an average time of 4.18 minutes to retrieve a match list. This compares favorably with the existing technique shape-based (edge direction histogram) method which has the performance rates of 29% and 46% in the 1 and 5 top ranks respectively.;In summary, the proposed ADIS system accurately retrieves the dental record with an overall rate of 80% in top 5 ranks when a candidate list of 20 is used (from potential match search) whereas a candidate size of 10 yields an overall rate of 84% in top 5 ranks and takes only a few minutes to search the database, which compares favorably against most of the existing methods in the literature, when both accuracy and computational complexity are considered

Do You Mind? User Perceptions of Machine Consciousness

The prospect of machine consciousness cultivates controversy across media, academia, and industry. Assessing whether non-experts perceive technologies as conscious, and exploring the consequences of this perception, are yet unaddressed challenges in Human Computer Interaction (HCI). To address them, we surveyed 100 people, exploring their conceptualisations of consciousness and if and how they perceive consciousness in currently available interactive technologies. We show that many people already perceive a degree of consciousness in GPT-3, a voice chat bot, and a robot vacuum cleaner. Within participant responses we identified dynamic tensions between denial and speculation, thinking and feeling, interaction and experience, control and independence, and rigidity and spontaneity. These tensions can inform future research into perceptions of machine consciousness and the challenges it represents for HCI. With both empirical and theoretical contributions, this paper emphasises the importance of HCI in an era of machine consciousness, real, perceived or denied

Do You Mind? User Perceptions of Machine Consciousness

The prospect of machine consciousness cultivates controversy across media, academia, and industry. Assessing whether non-experts perceive technologies as conscious, and exploring the consequences of this perception, are yet unaddressed challenges in Human Computer Interaction (HCI). To address them, we surveyed 100 people, exploring their conceptualisations of consciousness and if and how they perceive consciousness in currently available interactive technologies. We show that many people already perceive a degree of consciousness in GPT-3, a voice chat bot, and a robot vacuum cleaner. Within participant responses we identified dynamic tensions between denial and speculation, thinking and feeling, interaction and experience, control and independence, and rigidity and spontaneity. These tensions can inform future research into perceptions of machine consciousness and the challenges it represents for HCI. With both empirical and theoretical contributions, this paper emphasises the importance of HCI in an era of machine consciousness, real, perceived or denied