Automatic vs Manual Provenance Abstractions: Mind the Gap

In recent years the need to simplify or to hide sensitive information in provenance has given way to research on provenance abstraction. In the context of scientific workflows, existing research provides techniques to semi automatically create abstractions of a given workflow description, which is in turn used as filters over the workflow's provenance traces. An alternative approach that is commonly adopted by scientists is to build workflows with abstractions embedded into the workflow's design, such as using sub-workflows. This paper reports on the comparison of manual versus semi-automated approaches in a context where result abstractions are used to filter report-worthy results of computational scientific analyses. Specifically; we take a real-world workflow containing user-created design abstractions and compare these with abstractions created by ZOOM UserViews and Workflow Summaries systems. Our comparison shows that semi-automatic and manual approaches largely overlap from a process perspective, meanwhile, there is a dramatic mismatch in terms of data artefacts retained in an abstracted account of derivation. We discuss reasons and suggest future research directions.Comment: Preprint accepted to the 2016 workshop on the Theory and Applications of Provenance, TAPP 201

Putting Instruction Sequences into Effect

An attempt is made to define the concept of execution of an instruction sequence. It is found to be a special case of directly putting into effect of an instruction sequence. Directly putting into effect of an instruction sequences comprises interpretation as well as execution. Directly putting into effect is a special case of putting into effect with other special cases classified as indirectly putting into effect

Interface groups and financial transfer architectures

Analytic execution architectures have been proposed by the same authors as a means to conceptualize the cooperation between heterogeneous collectives of components such as programs, threads, states and services. Interface groups have been proposed as a means to formalize interface information concerning analytic execution architectures. These concepts are adapted to organization architectures with a focus on financial transfers. Interface groups (and monoids) now provide a technique to combine interface elements into interfaces with the flexibility to distinguish between directions of flow dependent on entity naming. The main principle exploiting interface groups is that when composing a closed system of a collection of interacting components, the sum of their interfaces must vanish in the interface group modulo reflection. This certainly matters for financial transfer interfaces. As an example of this, we specify an interface group and within it some specific interfaces concerning the financial transfer architecture for a part of our local academic organization. Financial transfer interface groups arise as a special case of more general service architecture interfaces.Comment: 22 page

Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department

BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, emergency department encounters in order to deliver appropriate care and referrals. Unfortunately, falls are difficult to identify without manual chart review, a time intensive process infeasible for many applications including surveillance and quality reporting. Here we describe a pragmatic NLP approach to automating fall identification. METHODS: In this single center retrospective review, 500 emergency department provider notes from older adult patients (age 65 and older) were randomly selected for analysis. A simple, rules-based NLP algorithm for fall identification was developed and evaluated on a development set of 1084 notes, then compared with identification by consensus of trained abstractors blinded to NLP results. RESULTS: The NLP pipeline demonstrated a recall (sensitivity) of 95.8%, specificity of 97.4%, precision of 92.0%, and F1 score of 0.939 for identifying fall events within emergency physician visit notes, as compared to gold standard manual abstraction by human coders. CONCLUSIONS: Our pragmatic NLP algorithm was able to identify falls in ED notes with excellent precision and recall, comparable to that of more labor-intensive manual abstraction. This finding offers promise not just for improving research methods, but as a potential for identifying patients for targeted interventions, quality measure development and epidemiologic surveillance

A retrospective study of breast milk feeding in infants with oral clefts

OBJECTIVE: The goal of this study was to gather information from mothers’ of children born with orofacial clefts (OFC) in order to more accurately describe their early feeding experiences, from the time of diagnosis through the first six months of life. METHODS: We surveyed mother’s whose babies with OFC were treated at Seattle Children’s Hospital (SCH) Craniofacial Clinic and were born on or after 1/1/2013 through 12/31/2016. Survey questions were geared toward understanding overall difficulty with feeding, access to supplies for feeding, and methods and duration of any breast milk feeding. RESULTS: Eighty-two percent of mothers wanted to exclusively breastfeed for the first 16 weeks prior to the OFC diagnosis, of which 79% attempted breastfeeding and 74% attempted any breast milk feeding. Donor milk was used in 18% of mothers and 41% supplemented with formula in the delivery hospital. The majority of women were knowledgeable about facts of breastfeeding and 41% reported they received information from a lactation specialist in their delivery hospital. The level of stress reported by mothers stayed relatively the same over first 4 weeks of life and dropped by 16 weeks. The majority of women who used a breast pump pumped for 0 to 20 minutes in first week and then 0 to 30 minutes between weeks 4 to 16. Thirty percent of mothers reported receiving information specifically from a craniofacial nurse and craniofacial pediatrician before delivery and 36% reported receiving information from a craniofacial nurse and craniofacial pediatrician after their birth hospital stay. CONCLUSION: Initial study results of feeding practices, knowledge of breast milk feeding, and feeding experiences of mothers with babies born with OFCs show that most mother’s intended to exclusively breastfeed prior to their birth and that the majority of women were reasonably informed about the benefits of breastfeeding. We also found that after the delivery of their child with an OFC more mothers reported having difficulty with feeding and wanted to provide breast milk longer than they were able to do so. Once the data collection is complete the survey data will be stratified for prenatal versus postnatal diagnosis and also when a breast pump was obtained. This information and additional data will be collected from a second phase of the study, which is a medical chart abstraction to look at the child’s demographics and growth chart data for the first six months of life

Architectural implications for context adaptive smart spaces

Buildings and spaces are complex entities containing complex social structures and interactions. A smart space is a composite of the users that inhabit it, the IT infrastructure that supports it, and the sensors and appliances that service it. Rather than separating the IT from the buildings and from the appliances that inhabit them and treating them as separate systems, pervasive computing combines them and allows them to interact. We outline a reactive context architecture that supports this vision of integrated smart spaces and explore some implications for building large-scale pervasive systems

Formalising responsibility modelling for automatic analysis

Modelling the structure of social-technical systems as a basis for informing software system design is a difficult compromise. Formal methods struggle to capture the scale and complexity of the heterogeneous organisations that use technical systems. Conversely, informal approaches lack the rigour needed to inform the software design and construction process or enable automated analysis. We revisit the concept of responsibility modelling, which models social technical systems as a collection of actors who discharge their responsibilities, whilst using and producing resources in the process. Responsibility modelling is formalised as a structured approach for socio-technical system requirements specification and modelling, with well-defined semantics and support for automated structure and validity analysis. The effectiveness of the approach is demonstrated by two case studies of software engineering methodologies

Understanding Disease Heterogeneity and Patient Characteristics in Patients with Amyotrophic Lateral Sclerosis (ALS)

Background: Amytrophic lateral sclerosis (ALS) is a fatal neurologic disease that is projected to double in worldwide incidence in the next 20 years. The heterogenic nature of the disease and relatively limited research data, compared to non-rare diseases, have made it difficult for clinician researchers to alter the course of the disease within the short life expectancy after symptom onset. Method: This was a mixed-method retrospective review and live sampling study using three distinct data sources. Retrospective data was abstracted from the electronic medical record systems for a select group of ALS patients seen at the University of California, Irvine Neuromuscular Center (UCI NMC). Additional retrospective datasets curated by the Pooled Resources Open-Access Clinical Trials (PRO-ACT) database were also analyzed. Observational data was collected using a 9-item survey developed on Google Forms and disseminated through the ALS Association Golden West Chapter. The items measured symptom onset, diagnostic journey, and patient demographics.Results: The analyses confirmed current reports of higher disease incidence in Caucasian populations, usually comprising at least 60% of each dataset. The gender prevalence towards males was only observed in the PRO-ACT dataset. There was also a difference in mean age between PRO-ACT (56 years), UCI (61 years), and Online Questionnaire respondents (66 years). Discussion: Ultimately retrospective data analyses were limited by substantial missing, not at random data. Large data repositories can bridge the gap between non-rare and rare disease research, but only with robust and methodologic data collection across all participating sites

Advanced Architectures for Transactional Workflows or Advanced Transactions in Workflow Architectures

In this short paper, we outline the workflow management systems research in the Information Systems division at the University of Twente. We discuss the two main themes in this research: architecture design and advanced transaction management. Attention is paid to the coverage of these themes in the context of the completed Mercurius and WIDE projects and in the new CrossFlow project. In the latter project, contracts are introduced as a new theme to support electronic commerce aspects in workflow management