This thesis is an exploration of the work I have completed during graduate study at UNO. My time has been spent investigating concepts of evaluation and the attribution of meaning. The main thrust and impetus of my art has been to explore the subjective way people interpret visual language and how that interpretation can be manipulated and undermined. By undoing these associations I hope to reveal the tentative nature of meaning.

The objective of the proposed research is to answer the question of how to provide verification and redactability to medical documents at a manageable computation cost to all parties involved. The approach for this solution examines the use of Merkle Hash Trees to provide the redaction and verification characteristics required. Using the Merkle Hash Tree, various Continuity of Care Documents will have their various elements extracted for storage in the signature scheme. An analysis of the approach and the various characteristics that made this approach a likely candidate for success are provided within. A description of a framework implementation and a sample application are provided to demonstrate potential uses of the system. Finally, results seen from various experiments with the framework are included to provide concrete evidence of a solution to the question which was the focus of this research.

The amount of knowledge increases rapidly due to the increasing number of available data sources. However, the autonomy of data sources and the resulting heterogeneity prevent comprehensive data analysis and applications. Data integration aims to overcome heterogeneity by unifying different data sources and enriching unstructured data. The enrichment of data consists of different subtasks, amongst other the annotation process. The annotation process links document phrases to terms of a standardized vocabulary. Annotated documents enable effective retrieval methods, comparability of different documents, and comprehensive data analysis, such as finding adversarial drug effects based on patient data. A vocabulary allows the comparability using standardized terms. An ontology can also represent a vocabulary, whereas concepts, relationships, and logical constraints additionally define an ontology. The annotation process is applicable in different domains. Nevertheless, there is a difference between generic and specialized domains according to the annotation process. This thesis emphasizes the differences between the domains and addresses the identified challenges. The majority of annotation approaches focuses on the evaluation of general domains, such as Wikipedia. This thesis evaluates the developed annotation approaches with case report forms that are medical documents for examining clinical trials. The natural language provides different challenges, such as similar meanings using different phrases. The proposed annotation method, AnnoMap, considers the fuzziness of natural language. A further challenge is the reuse of verified annotations. Existing annotations represent knowledge that can be reused for further annotation processes. AnnoMap consists of a reuse strategy that utilizes verified annotations to link new documents to appropriate concepts. Due to the broad spectrum of areas in the biomedical domain, different tools exist. The tools perform differently regarding a particular domain. This thesis proposes a combination approach to unify results from different tools. The method utilizes existing tool results to build a classification model that can classify new annotations as correct or incorrect. The results show that the reuse and the machine learning-based combination improve the annotation quality compared to existing approaches focussing on the biomedical domain. A further part of data integration is entity resolution to build unified knowledge bases from different data sources. A data source consists of a set of records characterized by attributes. The goal of entity resolution is to identify records representing the same real-world entity. Many methods focus on linking data sources consisting of records being characterized by attributes. Nevertheless, only a few methods can handle graph-structured knowledge bases or consider temporal aspects. The temporal aspects are essential to identify the same entities over different time intervals since these aspects underlie certain conditions. Moreover, records can be related to other records so that a small graph structure exists for each record. These small graphs can be linked to each other if they represent the same. This thesis proposes an entity resolution approach for census data consisting of person records for different time intervals. The approach also considers the graph structure of persons given by family relationships. For achieving qualitative results, current methods apply machine-learning techniques to classify record pairs as the same entity. The classification task used a model that is generated by training data. In this case, the training data is a set of record pairs that are labeled as a duplicate or not. Nevertheless, the generation of training data is a time-consuming task so that active learning techniques are relevant for reducing the number of training examples. The entity resolution method for temporal graph-structured data shows an improvement compared to previous collective entity resolution approaches. The developed active learning approach achieves comparable results to supervised learning methods and outperforms other limited budget active learning methods. Besides the entity resolution approach, the thesis introduces the concept of evolution operators for communities. These operators can express the dynamics of communities and individuals. For instance, we can formulate that two communities merged or split over time. Moreover, the operators allow observing the history of individuals. Overall, the presented annotation approaches generate qualitative annotations for medical forms. The annotations enable comprehensive analysis across different data sources as well as accurate queries. The proposed entity resolution approaches improve existing ones so that they contribute to the generation of qualitative knowledge graphs and data analysis tasks.

Ce mémoire examine les pratiques des demandeurs d’asile dans les structures humanitaires médicales de l’île de Lesvos, en Grèce. Maintenus dans la zone-frontière que constitue l'île, les demandeurs d’asile vivent dans le camp de Moria, reconnu pour ses conditions de vie extrêmement mauvaises. Dans le cadre de leur processus d’asile, ils sont soumis à une procédure médicale, l’évaluation de vulnérabilité, dont le résultat influence leurs parcours. Dans le cadre d’un terrain ethnographique mené sur l’île à l’été 2018, j’ai effectué de la participation observante en tant qu’interprète au sein d’une clinique humanitaire, où des médecins bénévoles et des demandeurs d’asile négocient ensemble le pouvoir attribué à l’évaluation de vulnérabilité. Le mémoire analyse les pratiques des demandeurs d’asile à partir du concept d’agentivité circonscrite, une forme d'agentivité aux effets imprévisibles. Dans une première partie, je démontre que les demandeurs d’asile mettent en œuvre des stratégies pour négocier la situation inhumaine dans laquelle ils sont mis ainsi que pour obtenir une reconnaissance. Leurs stratégies se structurent autour d’une réappropriation des logiques du dispositif humanitaire, notamment des stéréotypes qui sont assignés aux réfugiés. Dans une seconde partie, j’examine en profondeur un élément de ces stratégies qui est central aux interactions de soin dans la clinique humanitaire : les documents médicaux. Je montre que ces documents sont une technologie flexible dont la fonction est détournée par les pratiques des demandeurs d’asile, qui les utilisent comme une ressource et comme une preuve. Finalement, j’analyse les différentes façons dont les médecins bénévoles réagissent à ces pratiques ainsi que leurs conséquences sur l’accès aux soins médicaux. Ces éléments établissent un portrait nuancé des effets du dispositif humanitaire établi aux frontières de l’Europe suite à la crise des réfugiés de 2015. / This study examines asylum seekers’ practices within medical humanitarian structures on Lesvos island, Greece. Maintained inside the border-zone constituted by the island, asylum seekers live in Moria camp, which is known for its extremely bad living conditions. In the context of their asylum process, they undergo a medical procedure, the vulnerability assessment, the result of which influences their trajectories. As part of an ethnographic fieldwork conducted on the island in the summer of 2018, I carried out observing participation as an interpreter in a humanitarian clinic, a space where volunteer doctors and asylum seekers negotiate the power attributed to the vulnerability assessment. This study analyses the practices of asylum seekers through the concept of circumscribed agency, which effects are unpredictable. I first show that asylum seekers set up strategies to negotiate the inhuman situation in which they find themselves, as well as to obtain recognition. Their strategies are structured around a reappropriation of the logics of the humanitarian device, notably the stereotypes assigned to refugees. The second part extensively examines an element of these strategies central to the care interactions taking place in the humanitarian clinic: the medical documents. I show that these documents act as a flexible technology and that their function is reconfigured by asylum seekers’ practices, who use them as resources and proofs. Finally, I highlight the different ways in which volunteer doctors react to these practices, along with their consequences on access to medical care. These elements provide a nuanced description of the effects of the humanitarian device established at Europe’s borders following the 2015 refugee crisis.