Human-Data Interaction in Healthcare

In this paper, we focus on an emerging strand of IT-oriented research, namely Human-Data Interaction (HDI) and how this can be applied to healthcare. HDI regards both how humans create and use data by means of interactive systems, which can both assist and constrain them, as well as to passively collect and proactively generate data. Healthcare provides a challenging arena to test the potential of HDI to provide a new, user-centered perspective on how data work should be supported and assessed, especially in the light of the fact that data are becoming increasingly big and that many tools are now available for the lay people, including doctors and nurses, to interact with health-related data.Comment: 10 pages, 4 Figure

Context-based ontology matching and data interlinking

euzenat2015cContext-based matching finds correspondences between entities from two ontologies by relating them to other resources. A general view of context-based matching is designed by analysing existing such matchers. This view is instantiated in a path-driven approach that (a) anchors the ontologies to external ontologies, (b) finds sequences of entities (path) that relate entities to match within and across these resources, and (c) uses algebras of relations for combining the relations obtained along these paths. Parameters governing such a system are identified and made explicit. We discuss the extension of this approach to data interlinking and its benefit to cross-lingual data interlinking. First, this extension would require an hybrid algebra of relation that combines relations between individual and classes. However, such an algebra may not be particularly useful in practice as only in a few restricted case it could conclude that two individuals are the same. But it can be used for finding mistakes in link sets

Using Locally Weighted Regression to Estimate the Functional Size of Software: an Empirical Study

In software engineering, measuring software functional size via the IFPUG (International Function Point Users Group) Function Point Analysis using the standard manual process can be a long and expensive activity, which is possible only when functional user requirements are known completely and in detail. To solve this problem, several early estimation methods have been proposed and have become de facto standard processes. Among these, a prominent one is High-level Function Point Analysis. Recently, the Simple Function Point method has been released by IFPUG; although it is a proper measurement method, it has a great level of convertibility to traditional Function Points and may be used as an estimation method. Both High-level Function Point Analysis and Simple Function Point skip the activities needed to weight data and transaction functions, thus enabling lightweight measurement based on coarse-grained requirements specifications. This makes the process faster and cheaper, but yields approximate measures. The accuracy of the mentioned method has been evaluated, also via large-scale empirical studies, showing that the yielded approximate measures are sufficiently accurate for practical usage. In this paper, locally weighted regression is applied to the problem outlined above. This empirical study shows that estimates obtained via locally weighted regression are more accurate than those obtained via High-level Function Point Analysis, but are not substantially better than those yielded by alternative estimation methods using linear regression. The Simple Function Point method appears to yield measures that are well correlated with those obtained via standard measurement. In conclusion, locally weighted regression appears to be effective and accurate enough for estimating software functional size

IGV Short Scale to Assess Implicit Value of Visualizations through Explicit Interaction

This paper reports the assessment of the infographics-value (IGV) short scale, designed to measure the value in the use of infographics. The scale was made to assess the implicit quality dimensions of infographics. These dimensions were experienced during the execution of tasks in a contextualized scenario. Users were asked to retrieve a piece of information by explicitly interacting with the infographics. After usage, they were asked to rate quality dimensions of infographics, namely, usefulness, intuitiveness, clarity, informativity, and beauty; the overall value perceived from interacting with infographics was also included in the survey. Each quality dimension was coded as a six-point rating scale item, with overall value included. The proposed IGV short scale model was validated with 650 people. Our analysis confirmed that all considered dimensions in our scale were independently significant and contributed to assessing the implicit value of infographics. The IGV short scale is a lightweight but exhaustive tool to rapidly assess the implicit value of an explicit interaction with infographics in daily tasks, where value in use is crucial to measuring the situated effectiveness of visual tools. View Full-Tex

Bridging Objective and Subjective Evaluations in Data Visualization: A Crossover Experiment

One of the problems affecting evaluation in the design and adoption of HCI technology is that neither objective nor subjective measures are sufficient when taken alone or individually. This paper proposes a crossover approach, making sense of objective and subjective evaluation methods by hypothesizing them as constitutive of each other’s explanation. Objective image features borrowed from image processing may explain or being explained in terms of validated qualitative items for infographics value-in-use and qualitative labelling from users’ interaction. These methods are all applied to the evaluation of a small set of Data Vizualizations (Data Viz from now on). Image features are computed first, in order to provide a varied-features Data Viz selection from researchers; the subjective part of the evaluation is accomplished by the 98 participants of an experiment, who interacted with pairs of Data Viz by executing a task, then using the validated items of the Infographics-Value (IGV) short scale, and adding free qualitative comments. Crossing over these dimensions shows that: a high feature congestion in a Data Viz can hinder its perceived intuitiveness and clarity; a poorly distributed saliency may impact intuitiveness and clarity too; a high colorfulness may influence the perceived beauty; both saliency and colorfulness may impact on the perceived usefulness, informativity, and beauty. Furthermore, colorfulness can improve or worsen the perceived overall quality of design and quality of interaction when used and combined with feature congestion; and saliency may improve or worsen the perceived beauty when interacting with colorfulness. These results show how objective and subjective evaluations may be exploited as each other’s explanations for improving the evaluation process during both design and user experience with Data Viz. Based on this experiment, the importance of crossing-over quantitative and qualitative Data Viz evaluation is argued, and motivations to the exploitation of a combination of approaches instead of the application of one approach alone are supported. This contribution intends to lead towards a holistic Data Viz quality assessment method, able to provide a virtuous cycle enforcing both quantitative and qualitative approaches during all the phases of a Data Viz evaluation life

Machine Learning in Orthopedics: A Literature Review

In this paper we present the findings of a systematic literature review covering the articles published in the last two decades in which the authors described the application of a machine learning technique and method to an orthopedic problem or purpose. By searching both in the Scopus and Medline databases, we retrieved, screened and analyzed the content of 70 journal articles, and coded these resources following an iterative method within a Grounded Theory approach. We report the survey findings by outlining the articles' content in terms of the main machine learning techniques mentioned therein, the orthopedic application domains, the source data and the quality of their predictive performance

Representable AI: Towards a Unified View of Core Dimensions for a Visual Framework

International audienceData visualization made of multiple visualization techniques, e.g., dashboards and small multiples, is taking the scene as data, AI algorithms and their analysis are becoming more complex and articulated. However, still too little is said about what are the core dimensions of these interactions that may contribute to characterize visualization techniques orchestration in scenarios where humans and AI work together and communicate through visual languages, and what is the differential in complexity with respect to single charts interaction. Depending on such dimensions, their level, and their combination, interaction may require a cognitively growing effort. The present study aims at giving a unified view of complex visual frameworks in order to identify the invariants of visualization techniques characterization, and proposes a group of necessary and sufficient dimensions emerging when visualization techniques are the focus of the design and may be the focus of interaction between humans and AI. The paper identifies and discusses these dimensions, starting from the literature, and giving a characterization of each of them in terms of constituent levels. The framework may be applied to analysis of a range of data visualization tools and approaches, towards their concrete application to a distributed visual cognition framework where humans-AI interactions will take place

Context-based ontology matching and data interlinking

euzenat2015cContext-based matching finds correspondences between entities from two ontologies by relating them to other resources. A general view of context-based matching is designed by analysing existing such matchers. This view is instantiated in a path-driven approach that (a) anchors the ontologies to external ontologies, (b) finds sequences of entities (path) that relate entities to match within and across these resources, and (c) uses algebras of relations for combining the relations obtained along these paths. Parameters governing such a system are identified and made explicit. We discuss the extension of this approach to data interlinking and its benefit to cross-lingual data interlinking. First, this extension would require an hybrid algebra of relation that combines relations between individual and classes. However, such an algebra may not be particularly useful in practice as only in a few restricted case it could conclude that two individuals are the same. But it can be used for finding mistakes in link sets

Monitoraggio Ambientale di un'Area Contaminata nella Provincia di Pavia

Lo scopo di tale indagine è stato quello di valutare il livello di contaminazione, l'estensione e l'entità di contaminanti presenti nei suoli superficiali a suo tempo riscontrati mediante il Progetto Pavia. Il monitoraggio ambientale ha interessato un'area di circa 12 ettari che si trova nel comune di Carpiano. Complessivamente sono state identificate 33 aree di campionamento dove sono stati prelevati campioni di suolo sino alla profondità di 30 cm. In ciascun campione di suolo, dopo adeguati trattamenti, è stata valutata la concentrazione di metalli pesanti, metalloidi, macroelementi, sostanza organica, pH, densità apparente, contenuto d'acqua. In alcuni campioni, precisamente 11, si è analizzata la concentrazione di diossine e furani e si è approntato uno studio che ha visto l'utilizzo dei batteri e dei loro prodotti. Lo studio condotto attraverso l'uso dei batteri ha evidenziato anomalie in alcuni punti ad elevata contaminazione. I risultati analitici ottenuti hanno identificato la presenza di una importante contaminazione di metalli pesanti, metalloidi, diossine e furani che interessa un area di alcuni ettari. Tale livello di contaminazione, per la presenza di sostanza organica e per valori ridotti di acidità dei suoli stessi, potrà arrecare danni ingenti all'ambiente.JRC.DDG.H.7-Land management and natural hazard