The Network Turn

This Element contends that networks are a category of study that cuts across traditional academic barriers, uniting diverse disciplines through a shared understanding of complexity in our world. This title is also available as Open Access on Cambridge Core

Digits: Two Reports on New Units of Scholarly Publication

The Digits team (Matt Burton, Matthew J. Lavin, Jessica Otis, and Scott B. Weingart) convened around the question of how we might share, preserve, and legitimize scholarship freed from the affordances of print. For the A.W. Mellon-funded Digits Planning Grant (2016-2018), the PIs had three goals: - Investigate the use of software containers for research in the sciences, social sciences, and humanities. - Assess the infrastructural needs of digital humanists around publishing and preserving web-centric scholarship. - Gather a team of experts to guide the above activities and plan how they might inform a beneficial intervention into the scholarly ecosystem. Through our investigation into the scholarly uses of containers, we discovered that the technical infrastructure needed to connect containers with digital publications is underdeveloped. We see potential for container technologies to facilitate existing digital scholarly publications and afford new forms of computational scholarship, but this process would first require a series of infrastructural bridges. The digital scholarship needs assessment we conducted, as well as our advisory board meetings, made it clear that a targeted technological intervention alone would not be enough to welcome web-first publications into the scholarly ecosystem; in-tandem cultural and institutional changes are also necessary

Towards Interoperable Network Ontologies for the Digital Humanities

Scholars have long been interested in networks. Networks of scholarly exchange, trade, kinship, and patronage are some of the many such longstanding subjects of study. Recent and ongoing digital humanities projects are now considering networks with fresh approaches and increasingly complex datasets. At the heart of these digital projects are ‘network ontologies’ — functional data models for distilling the complicated, messy connections between historical people, objects, and places. Although scholars creating network ontologies necessarily focus on different types of content, if these networks are to form a coherent body of scholarship in the future, we must work towards the creation of interoperable ontological structures, rather than yet another set of competing standards. Here we examine the methodological considerations behind designing such interoperable ontologies, focusing primarily on the example of Early Modern historical networks. We argue that it would be infeasible to adopt a single ontological standard for all possible digital humanities projects; flexibility is essential to accommodate all subjects and objects of humanistic enquiry, from the micro-level to the longue-durée. However, we believe it possible to establish shared practices to structure these network ontologies on an ongoing basis in order to ensure their long-term interoperability

Uncertainty in humanities network visualization

Network visualization is one of the most widely used tools in digital humanities research. The idea of uncertain or “fuzzy” data is also a core notion in digital humanities research. Yet network visualizations in digital humanities do not always prominently represent uncertainty. In this article, we present a mathematical and logical model of uncertainty as a range of values which can be used in network visualizations. We review some of the principles for visualizing uncertainty of different kinds, visual variables that can be used for representing uncertainty, and how these variables have been used to represent different data types in visualizations drawn from a range of non-humanities fields like climate science and bioinformatics. We then provide examples of two diagrams: one in which the variables displaying degrees of uncertainty are integrated/pinto the graph and one in which glyphs are added to represent data certainty and uncertainty. Finally, we discuss how probabilistic data and what-if scenarios could be used to expand the representation of uncertainty in humanities network visualizations

Patient safety in primary care: a survey of general practitioners in the Netherlands

Contains fulltext : 89814.pdf (publisher's version ) (Open Access)BACKGROUND: Primary care encompasses many different clinical domains and patient groups, which means that patient safety in primary care may be equally broad. Previous research on safety in primary care has focused on medication safety and incident reporting. In this study, the views of general practitioners (GPs) on patient safety were examined. METHODS: A web-based survey of a sample of GPs was undertaken. The items were derived from aspects of patient safety issues identified in a prior interview study. The questionnaire used 10 clinical cases and 15 potential risk factors to explore GPs' views on patient safety. RESULTS: A total of 68 GPs responded (51.5% response rate). None of the clinical cases was uniformly judged as particularly safe or unsafe by the GPs. Cases judged to be unsafe by a majority of the GPs concerned either the maintenance of medical records or prescription and monitoring of medication. Cases which only a few GPs judged as unsafe concerned hygiene, the diagnostic process, prevention and communication. The risk factors most frequently judged to constitute a threat to patient safety were a poor doctor-patient relationship, insufficient continuing education on the part of the GP and a patient age over 75 years. Language barriers and polypharmacy also scored high. Deviation from evidence-based guidelines and patient privacy in the reception/waiting room were not perceived as risk factors by most of the GPs. CONCLUSION: The views of GPs on safety and risk in primary care did not completely match those presented in published papers and policy documents. The GPs in the present study judged a broader range of factors than in previously published research on patient safety in primary care, including a poor doctor-patient relationship, to pose a potential threat to patient safety. Other risk factors such as infection prevention, deviation from guidelines and incident reporting were judged to be less relevant than by policy makers

The Equifinality of Archaeological Networks: an Agent-Based Exploratory Lab Approach

When we find an archaeological network, how can we explore the necessary versus contingent processes at play in the formation of that archaeological network? Given a set of circumstances or processes, what other possible network shapes could have emerged? This is the problem of equifinality, where many different means could potentially arrive at the same end result: the networks that we observe. This paper outlines how agent-based modelling can be used as a laboratory for exploring different processes of archaeological network formation. We begin by describing our best guess about how the (ancient) world worked, given our target materials (here, the networks of production and patronage surrounding the Roman brick industry in the hinterland of Rome). We then develop an agent-based model of the Roman extractive economy which generates different kinds of networks under various assumptions about how that economy works. The rules of the simulation are built upon the work of Bang (2006; 2008) who describes a model of the Roman economy which he calls the ‘imperial Bazaar’. The agents are allowed to interact, and the investigators compare the kinds of networks this description generates over an entire landscape of economic possibilities. By rigorously exploring this landscape, and comparing the resultant networks with those observed in the archaeological materials, the investigators will be able to employ the principle of equifinality to work out the representativeness of the archaeological network and thus the underlying processes

Development of an In Vitro Model for the Multi-Parametric Quantification of the Cellular Interactions between Candida Yeasts and Phagocytes

We developed a new in vitro model for a multi-parameter characterization of the time course interaction of Candida fungal cells with J774 murine macrophages and human neutrophils, based on the use of combined microscopy, fluorometry, flow cytometry and viability assays. Using fluorochromes specific to phagocytes and yeasts, we could accurately quantify various parameters simultaneously in a single infection experiment: at the individual cell level, we measured the association of phagocytes to fungal cells and phagocyte survival, and monitored in parallel the overall phagocytosis process by measuring the part of ingested fungal cells among the total fungal biomass that changed over time. Candida albicans, C. glabrata, and C. lusitaniae were used as a proof of concept: they exhibited species-specific differences in their association rate with phagocytes. The fungal biomass uptaken by the phagocytes differed significantly according to the Candida species. The measure of the survival of fungal and immune cells during the interaction showed that C. albicans was the more aggressive yeast in vitro, destroying the vast majority of the phagocytes within five hours. All three species of Candida were able to survive and to escape macrophage phagocytosis either by the intraphagocytic yeast-to-hyphae transition (C. albicans) and the fungal cell multiplication until phagocytes burst (C. glabrata, C. lusitaniae), or by the avoidance of phagocytosis (C. lusitaniae). We demonstrated that our model was sensitive enough to quantify small variations of the parameters of the interaction. The method has been conceived to be amenable to the high-throughput screening of mutants in order to unravel the molecular mechanisms involved in the interaction between yeasts and host phagocytes