Web-based Data Analysis Research Articles

Contribution of Family Nurses to the Success of Breastfeeding

Introduction: Breast milk is extremely important for maternal and child health bringing indisputable benefits to mother, family and society. Health professionals, including nurses, play a key role in promoting and supporting breastfeeding with all their technical-scientific knowledge and proximity to the population. Aims: Understand the mothers’ perspective regarding the contribution of health professionals to the success of breastfeeding. Methodology: Qualitative study with a phenomenological approach. Semi-structured interviews were conducted with 13 women from a Family Health Unit in a Primary care setting who were mothers between December 2016 and December 2017. A content analysis of the data was performed with the support of web-based data analysis (webQDA®) software. Results: The intervention of the family nurse in the context of pregnancy surveillance and child health consultations is distinguished, as well as in home visitation. The intervention of midwives in pre-natal courses and post-natal breastfeeding consultations also demonstrated to be relevant for breastfeeding success. Conclusion: As recommended by the World Health Organization and United Nations International Children’s Emergency Fund, an effort is being made by health professionals, including nurses and midwives, for support of mothers and families in the decision, establishment and maintenance of the breastfeeding process, contributing positively to its success and establishing a follow-up to woman and family throughout the pregnancy-puerperal cycle.

Integration of Free Floating Car Sharing Systems in Rail Stations: A Web Based Data Analysis

In the last decades, car sharing has been a tool for city planners to reduce private car traffic and pollution in big urban areas. The emergence of the ICTs (Information and Communication Technologies), together with the development of the collaborative economy, has allowed for the birth of the new Free-Floating Carsharing (FFCS): A more flexible type of carsharing, in which electric cars can be used. Little research has been devoted using real FFCS flows data, to the FFCS impacts on user behavior and even on the public transport system thus far. Furthermore, in big metropolitan areas, central rail stations should promote modal interchanges, including new modes of electric FFCS systems. The aim of this paper is to design a web-based platform to collect and analyze FFCS demand on the surrounding areas of rail stations and makes a proposal to provide these systems with electrical recharging energy obtained from the regenerative braking of high-speed trains. This case study includes Atocha and Chamartín Central Stations in Madrid (Spain). Scientific evidence shows a high demand of FFCS cars at central rail stations and a trip profile with a short time duration linked to the closest districts of rail stations.

Web-based data analytics framework for well forecasting and groundwater quality

Groundwater supplies drinking water for over one-third of all Americans. However, with aquifers stressed by overdraft, contamination from land use, and the hydrologic impacts of climate change, identifying reliable sources for new wells is increasingly challenging. Well forecasting is a process in which potential groundwater resources are evaluated for a location of interest. While this process forecasts the depth of each aquifer for a given location, it takes historical groundwater well data from nearby locations into account. Conventionally, well forecasting is done by geological survey professionals by manually analyzing the well data and, that makes the process both time and resource-intensive. This study presents a novel web application that performs well forecasting for any location within the state of Iowa in a matter of seconds utilizing client-side computing instead of expensive professional labor. The web application generates well forecasts by triangulating millions of combinations of historical aquifer depth data of nearby wells stored in a state-level database. The proposed web system also provides water quality information for arsenic, nitrate, and bacteria (total c and fecal coliform) on the same interface with forecasts. The system is open to the public and is aimed to provide a go-to tool for homeowners, well drillers and, authorities to help inform decision-making regarding groundwater well development and water quality monitoring efforts.

BaSDAS: a web-based pooled CRISPR-Cas9 knockout screening data analysis system.

We developed the BaSDAS (Barcode-Seq Data Analysis System), a GUI-based pooled knockout screening data analysis system, to facilitate the analysis of pooled knockout screen data easily and effectively by researchers with limited bioinformatics skills. The BaSDAS supports the analysis of various pooled screening libraries, including yeast, human, and mouse libraries, and provides many useful statistical and visualization functions with a user-friendly web interface for convenience. We expect that BaSDAS will be a useful tool for the analysis of genome-wide screening data and will support the development of novel drugs based on functional genomics information.

GcType: a high-quality type strain genome database for microbial phylogenetic and functional research.

Taxonomic and functional research of microorganisms has increasingly relied upon genome-based data and methods. As the depository of the Global Catalogue of Microorganisms (GCM) 10K prokaryotic type strain sequencing project, Global Catalogue of Type Strain (gcType) has published 1049 type strain genomes sequenced by the GCM 10K project which are preserved in global culture collections with a valid published status. Additionally, the information provided through gcType includes >12 000 publicly available type strain genome sequences from GenBank incorporated using quality control criteria and standard data annotation pipelines to form a high-quality reference database. This database integrates type strain sequences with their phenotypic information to facilitate phenotypic and genotypic analyses. Multiple formats of cross-genome searches and interactive interfaces have allowed extensive exploration of the database's resources. In this study, we describe web-based data analysis pipelines for genomic analyses and genome-based taxonomy, which could serve as a one-stop platform for the identification of prokaryotic species. The number of type strain genomes that are published will continue to increase as the GCM 10K project increases its collaboration with culture collections worldwide. Data of this project is shared with the International Nucleotide Sequence Database Collaboration. Access to gcType is free at http://gctype.wdcm.org/.

Pilot Survey for National Point Prevalence Study of Healthcare-Associated Infections in Acute-Care Hospitals in South Korea

Background: The Korean National Healthcare-Associated Infections Surveillance System (KONIS) was established to conduct nationwide surveillance of device-associated healthcare-associated infections (HAIs) and surgical site infections annually in 2006. However, no surveillance on overall HAIs has been conducted. Objective: We conducted a point-prevalence survey of total HAIs to estimate the incidence rate of HAIs in acute-care hospitals in South Korea. Methods: We defined HAIs according to KONIS and NHSN criteria. In total, 29 acute-care hospitals including 9 tertiary-care hospitals (TCHs) and 20 secondary-care hospitals (SCHs) were recruited as representing the population of every metropolitan city and province in South Korea. Patients who stayed at the hospitals on August 1, 2018, were randomly selected: 100 for SCHs and 200 for TCHs. Their medical records were retrospectively reviewed for HAIs according to the NHSN criteria by the infection control nurses (ICNs) from each hospital. A web-based data collection and analysis program was developed, and participating ICNs were educated in a 1-day training course with pre- and postevaluations. They received continuous feedback of input data and questions through the web-based system during the study. To generate estimates of the incidence rate of HAIs, we converted prevalence to incidence using the formula of Rhame and Sudderth. Results: Of 4,296 patients, 133 had ≥1 HAI (3.1%). In total, 141 HAIs were identified: gastrointestinal infections (n = 30, 21.3%), bloodstream infections (n = 30, 21.3%), pneumonia (n = 29, 20.6%), urinary tract infection (n =26, 18.4%). Among the gastrointestinal infections, C. difficile infections were the most common (17.7%). Device-associated infections accounted for 34.8% of all HAIs. The overall incidence of HAIs in TCHs was 4.39%, which was a higher incidence than SCHs (3.76%). Intensive care units had 12.6% of HAIs, whereas general wards had 3.4%. HAI incidences were 5.7%, 2.8%, and 2.3%, respectively, for each of the medical wards, surgical wards, and pediatric wards. The 3 most common pathogens were Escherichia coli, Acinetobacter baumannii, and Enterococcus faecium. Conclusions: The prevalence of HAI in Korea is lower than in most Western countries. The HAI burden of Clostridium difficile infection is surprisingly high, which calls for prompt control at the national level. To obtain national-level data on HAI burdens, ongoing surveillance is needed.Funding: NoneDisclosures: None

Interactive Web-based Data Visualization and Analysis Tool for Synthetizing on-farm Research Networks Data.

The on-farm research network concept enables a group of farmers to test new agricultural management practices under local conditions with support from local researchers or agronomists. Different on-farm trials based on the same experimental design are conducted over several years and sites to test the effectiveness of different innovative management practices aimed at increasing crop productivity and profitability. As a larger amount of historical trial data are being accumulated, data of all the trials require analyses and summarization. Summaries of on-farm trials are usually presented to farmers as individual field reports, which are not optimal for the dissemination of results and decision making. A more practical communication method is needed to enhance result communication and decision making. R Shiny is a new rapidly developing technology for turning R data analyses into interactive web applications. For the first time for on-farm research networks, we developed and launched an interactive web tool called ISOFAST using R Shiny. ISOFAST simultaneously reports all trial results about the same management practice to simplify interpretation of multi-site and multi-year summaries. We used a random-effects model to synthetize treatment differences at both the individual trial and network levels and generate new knowledge for farmers and agronomists. The friendly interface enables users to explore trial summaries, access model outputs, and perform economic analysis at their fingertips. This paper describes a case-study to illustrate how to use the tool and make agronomic management decisions based on the on-farm trial data. We also provided technical details and guidance for developing a similar interactive visualization tool customized for on-farm research network. ISOFAST is currently available at https://analytics.iasoybeans.com/cool-apps/ISOFAST/.

An open access mouse brain flatmap and upgraded rat and human brain flatmaps based on current reference atlases.

Here we present a flatmap of the mouse central nervous system (CNS) (brain) and substantially enhanced flatmaps of the rat and human brain. Also included are enhanced representations of nervous system white matter tracts, ganglia, and nerves, and an enhanced series of 10 flatmaps showing different stages of rat brain development. The adult mouse and rat brain flatmaps provide layered diagrammatic representation of CNS divisions, according to their arrangement in corresponding reference atlases: Brain Maps 4.0 (BM4, rat) (Swanson, The Journal of Comparative Neurology, 2018, 526, 935-943), and the first version of the Allen Reference Atlas (mouse) (Dong, The Allen reference atlas, (book + CD-ROM): A digital color brain atlas of the C57BL/6J male mouse, 2007). To facilitate comparative analysis, both flatmaps are scaled equally, and the divisional hierarchy of gray matter follows a topographic arrangement used in BM4. Also included with the mouse and rat brain flatmaps are cerebral cortex atlas level contours based on the reference atlases, and direct graphical and tabular comparison of regional parcellation. To encourage use of the brain flatmaps, they were designed and organized, with supporting reference tables, for ease-of-use and to be amenable to computational applications. We demonstrate how they can be adapted to represent novel parcellations resulting from experimental data, and we provide a proof-of-concept for how they could form the basis of a web-based graphical data viewer and analysis platform. The mouse, rat, and human brain flatmap vector graphics files (Adobe Reader/Acrobat viewable and Adobe Illustrator editable) and supporting tables are provided open access; they constitute a broadly applicable neuroscience toolbox resource for researchers seeking to map and perform comparative analysis of brain data.

An interactive web-based dashboard to track COVID-19 in Colombia. Case study: five main cities.

Design and implement an interactive web-based dashboard to track COVID-19 in Colombia. A tool was designed and implemented to analyze the data of Covid-19 positive cases in Colombia and published by the Instituto Nacional de Salud. The tool is based on the implementation of business intelligence methods with which you can understand the behavior of the pandemic in Colombia and generate structured data for decision-making by government levels. The tool displays, on a single screen, information on the number of cases, patient status, age ranges, city, location department, and gender. This information can be dynamically filtered and focus analyzes on the national, departmental, or municipal order. Additionally, methods are implemented for trend analysis, both on a linear and semi-log scale, as well as for calculating the case fatality rate in each of the municipalities. A web-based data analysis dashboard is implemented for semi-continuous monitoring of the COVID-19 pandemic in Colombia. With the use of the tool, a situational analysis is carried out for five of the most important cities in Colombia. The application is effective, flexible, and easy to use. The situational analysis reflects that public policies for the control of the disease have been favorable for Medellín, but for Cartagena, Bogotá, Barranquilla, and Cali, complementary measures are required.

DolphinNext: a distributed data processing platform for high throughput genomics

BackgroundThe emergence of high throughput technologies that produce vast amounts of genomic data, such as next-generation sequencing (NGS) is transforming biological research. The dramatic increase in the volume of data, the variety and continuous change of data processing tools, algorithms and databases make analysis the main bottleneck for scientific discovery. The processing of high throughput datasets typically involves many different computational programs, each of which performs a specific step in a pipeline. Given the wide range of applications and organizational infrastructures, there is a great need for highly parallel, flexible, portable, and reproducible data processing frameworks.Several platforms currently exist for the design and execution of complex pipelines. Unfortunately, current platforms lack the necessary combination of parallelism, portability, flexibility and/or reproducibility that are required by the current research environment. To address these shortcomings, workflow frameworks that provide a platform to develop and share portable pipelines have recently arisen. We complement these new platforms by providing a graphical user interface to create, maintain, and execute complex pipelines. Such a platform will simplify robust and reproducible workflow creation for non-technical users as well as provide a robust platform to maintain pipelines for large organizations.ResultsTo simplify development, maintenance, and execution of complex pipelines we created DolphinNext. DolphinNext facilitates building and deployment of complex pipelines using a modular approach implemented in a graphical interface that relies on the powerful Nextflow workflow framework by providing 1. A drag and drop user interface that visualizes pipelines and allows users to create pipelines without familiarity in underlying programming languages. 2. Modules to execute and monitor pipelines in distributed computing environments such as high-performance clusters and/or cloud 3. Reproducible pipelines with version tracking and stand-alone versions that can be run independently. 4. Modular process design with process revisioning support to increase reusability and pipeline development efficiency. 5. Pipeline sharing with GitHub and automated testing 6. Extensive reports with R-markdown and shiny support for interactive data visualization and analysis.ConclusionDolphinNext is a flexible, intuitive, web-based data processing and analysis platform that enables creating, deploying, sharing, and executing complex Nextflow pipelines with extensive revisioning and interactive reporting to enhance reproducible results.

Does Metal Hypersensitivity Have Relevance in Patients Undergoing TMJ Prosthetic Replacement?

Although concerns regarding implant-related metal hypersensitivity exist, no guidelines have been accepted for screening or treatment of patients with metal sensitivity before temporomandibular joint replacement (TMJR). The present study aimed to determine the trends in TMJR metal sensitivity screening and the effect of positive test results on patient treatment. A questionnaire was distributed to members of the American Society of Temporomandibular Joint Surgeons and the European Society of Temporomandibular Joint Surgeons using a web-based data collection and analysis tool. The questions aimed to establish the screening methods used to establish a diagnosis of metal hypersensitivity and any changes in management when metal hypersensitivity had been documented. A total of 72 responses (32.43%) were collected through the survey, with respondents primarily practicing in the United States (47.22%). Of the participants, 75% believed that metal hypersensitivity occurs with TMJR and only 2.77% did not. Most agreed that patients should be questioned about any metal sensitivities before consideration for TMJR (91.66%), and 80.55% routinely asked their patients if they had a previous sensitivity to any metals. Nickel was the most commonly encountered metal allergen (64.28%). If a metal allergy were reported, 44.28% of surgeons would refer the patient to determine the specific metal allergen. The diagnosis for metal allergy was based primarily on patient signs and symptoms (52.85%) and an allergist or dermatologist consultation (44.28%). The lymphocyte transformation test was the test most used by respondents to confirm the diagnosis. Of the surgeons, 41.42% would choose to observe/monitor as their first choice for patients testing positive for metal hypersensitivity. In the case of a "mild" reaction to metal hypersensitivity testing, 54.28% would alter their implant choice to a nonreactive metal component. For "severe" reactions to preoperative metal hypersensitivity testing, 62.85% would alter their implant choice to a nonreactive metal component, and 22.85% would choose not to perform TMJR. The results from the present study have demonstrated that respondent TMJ surgeons agree that metal hypersensitivity occurs with TMJR. However, their approaches to screening and managing metal hypersensitivity vary. Further research of this topic is required to eventually develop specific management pre- and postoperative guidelines for the treatment of patients with metal sensitivities.

A New Web-Based Big Data Analytics for Dynamic Public Opinion Mapping in Digital Networks on Contested Biotechnology Fields.

The expression "public opinion" has long been part of common parlance. However, its value as a scientific measure has been the topic of abundant academic debates over the past several decades. Such debates have produced more variety and contestations rather than consensus on the very definition of public opinion, let alone on how to measure it. This study reports on the usefulness of web-based big data digital network analytics in deciphering the distributed meanings and sense making related to controversial biotechnology applications. Using stem cell therapies as a case study, we argue that such digital network analysis can complement the traditional opinion polls while avoiding the sampling bias that is typical of opinion polls. Although the polls cannot account for the opinion dynamics, combining them with web-based big data analysis can shed light on three dimensions of public opinion essential for sense making: counts or volume of opinion data, content, and movement of opinions. This approach is particularly promising in the case of ongoing scientific controversies that increasingly overflow into the public sphere morphing into public political debates. In particular, our study focuses as a case study on public controversies over the clinical provision of stem cell therapies. Using web entities specifically addressing stem cell issues, including their dynamic aggregation, the internal architecture of the web corpus we report in this study brings the third dimension of public opinion (movement) into sharper focus. Notably, the corpus of stem cell networks through web connectivity presents hot spots of distributed meaning. Large-scale surveys conducted on these issues, such as the Eurobarometer of Biotechnology, reveal that European citizens only accept research on stem cells if they are highly regulated, while the stem cell digital network analysis presented in this study suggests that distributed meaning is promise centeredness. Although major scientific journals and companies tend to structure public opinion networks, our finding of promise centeredness as a key ingredient of distributed meaning and sense making is consistent with therapeutic tourism that remains as an important facet of the stem cell community despite the lack of material standards. This new approach to digital network analysis has crosscutting corollaries for rethinking the notion of public opinion, be it in electoral preferences or as we discuss in this study, for new ways to measure, monitor, and democratically govern emerging technologies.

ScienceBox Converging to Kubernetes containers in production for on-premise and hybrid clouds for CERNBox, SWAN, and EOS

Docker containers are the de-facto standard to package, distribute, and run applications on cloud-based infrastructures. Commercial providers and private clouds expand their offer with container orchestration engines, making the management of resources and containerized applications tightly integrated. The Storage Group of CERN IT leverages on container technologies to provide ScienceBox: An integrated software bundle with storage and computing services for general purposes and scientific use. ScienceBox features distributed scalable storage, sync&share functionalities, and a web-based data analysis service, and can be deployed on a single machine or scaled-out across multiple servers. ScienceBox has proven to be helpful in different contexts, from High Energy Physics analysis to education for high schools, and has been successfully deployed on different cloud infrastructure and heterogeneous hardware.

BEERE: a web server for biomedical entity expansion, ranking and explorations.

BEERE (Biomedical Entity Expansion, Ranking and Explorations) is a new web-based data analysis tool to help biomedical researchers characterize any input list of genes/proteins, biomedical terms or their combinations, i.e. ‘biomedical entities’, in the context of existing literature. Specifically, BEERE first aims to help users examine the credibility of known entity-to-entity associative or semantic relationships supported by database or literature references from the user input of a gene/term list. Then, it will help users uncover the relative importance of each entity—a gene or a term—within the user input by computing the ranking scores of all entities. At last, it will help users hypothesize new gene functions or genotype–phenotype associations by an interactive visual interface of constructed global entity relationship network. The output from BEERE includes: a list of the original entities matched with known relationships in databases; any expanded entities that may be generated from the analysis; the ranks and ranking scores reported with statistical significance for each entity; and an interactive graphical display of the gene or term network within data provenance annotations that link to external data sources. The web server is free and open to all users with no login requirement and can be accessed at http://discovery.informatics.uab.edu/beere/.

A Web-Based Form With Interactive Charts Used to Collect and Analyze Data on Home Births in Italy.

BackgroundThe use of Web-based forms and data analysis can improve the collection and visualization of data in clinical research. In Italy, no register exists that collects clinical data concerning home births.ObjectiveThe purpose of this study was (1) to develop a Web portal to collect, through a Web-based form, data on home births in Italy and (2) to provide those interested with a graphic visualization of the analyses and data collected.MethodsFollowing the World Health Organization’s guidelines, and adding questions based on scientific evidence, the case report form (CRF) on the online form was drafted by midwives of the National Association of Out-of-Hospital Birth Midwives. During an initial phase, a group of midwives (n=10) tested the CRF, leading to improvements and adding the necessary questions to achieve a CRF that would allow a more complete collection of data. After the test phase, the entire group of midwives (n=166) registered themselves on the system and began filling out birth questionnaires. In a subsequent phase, the administrators of the portal were able to view the completed forms in a graphic format through the use of interactive maps and graphs.ResultsFrom 2014 to 2016, 58 midwives included 599 birth questionnaires via the Web portal; of these, 443 were home-based, 76% (321/424) of which were performed at home and 24% (103/424) at a midwifery unit. Most of the births assisted (79%, 335/424) were in northern Italy, and the average ages of the mother and father were 33.6 (SD 4.7) years and 37.0 (SD 5.6) years, respectively.ConclusionsWe developed an innovative Web-based form that allows, for the first time in Italy, the collection of data on home births and births in the midwifery unit. Furthermore, the data collected are viewable online by the midwives through interactive maps and graphs that allow them to have a general and continuously updated view of the situation of out-of-hospital births performed by the National Association of Out-of-Hospital Birth Midwives. The future goal is to be able to expand this data collection to all out-of-hospital births throughout the national territory. With an increase in the number of enrolled midwives, it would be possible to use the portal as a Web-based form and also as a portal for sharing resources that would help midwives in their clinical practice.

Measuring the Impact of an Open Web-Based Prescribing Data Analysis Service on Clinical Practice: Cohort Study on NHS England Data.

BackgroundOpenPrescribing is a freely accessible service that enables any user to view and analyze the National Health Service (NHS) primary care prescribing data at the level of individual practices. This tool is intended to improve the quality, safety, and cost-effectiveness of prescribing.ObjectiveWe aimed to measure the impact of OpenPrescribing being viewed on subsequent prescribing.MethodsHaving preregistered our protocol and code, we measured three different metrics of prescribing quality (mean percentile across 34 existing OpenPrescribing quality measures, available “price-per-unit” savings, and total “low-priority prescribing” spend) to see whether they changed after the viewing of Clinical Commissioning Group (CCG) and practice pages. We also measured whether practices whose data were viewed on OpenPrescribing differed in prescribing, prior to viewing, compared with those who were not. We used fixed-effects and between-effects linear panel regression to isolate change over time and differences between practices, respectively. We adjusted for the month of prescribing in the fixed-effects model to remove underlying trends in outcome measures.ResultsWe found a reduction in available price-per-unit savings for both practices and CCGs after their pages were viewed. The saving was greater at practice level (−£40.42 per thousand patients per month; 95% CI −54.04 to −26.81) than at CCG level (−£14.70 per thousand patients per month; 95% CI −25.56 to −3.84). We estimate a total saving since launch of £243 thosand at practice level and £1.47 million at CCG level between the feature launch and end of follow-up (August to November 2017) among practices viewed. If the observed savings from practices viewed were extrapolated to all practices, this would generate £26.8 million in annual savings for the NHS, approximately 20% of the total possible savings from this method. The other two measures were not different after CCGs or practices were viewed. Practices that were viewed had worse prescribing quality scores overall prior to viewing.ConclusionsWe found a positive impact from the use of OpenPrescribing, specifically for the class of savings opportunities that can only be identified by using this tool. Furthermore, we show that it is possible to conduct a robust analysis of the impact of such a Web-based service on clinical practice.

GcMeta: a Global Catalogue of Metagenomics platform to support the archiving, standardization and analysis of microbiome data.

Meta-omics approaches have been increasingly used to study the structure and function of the microbial communities. A variety of large-scale collaborative projects are being conducted to encompass samples from diverse environments and habitats. This change has resulted in enormous demands for long-term data maintenance and capacity for data analysis. The Global Catalogue of Metagenomics (gcMeta) is a part of the ‘Chinese Academy of Sciences Initiative of Microbiome (CAS-CMI)’, which focuses on studying the human and environmental microbiome, establishing depositories of samples, strains and data, as well as promoting international collaboration. To accommodate and rationally organize massive datasets derived from several thousands of human and environmental microbiome samples, gcMeta features a database management system for archiving and publishing data in a standardized way. Another main feature is the integration of more than ninety web-based data analysis tools and workflows through a Docker platform which enables data analysis by using various operating systems. This platform has been rapidly expanding, and now hosts data from the CAS-CMI and a number of other ongoing research projects. In conclusion, this platform presents a powerful and user-friendly service to support worldwide collaborative efforts in the field of meta-omics research. This platform is freely accessible at https://gcmeta.wdcm.org/.

The Virtual-Spine Platform-Acquiring, visualizing, and analyzing individual sitting behavior.

Back pain is a serious medical problem especially for those people sitting over long periods during their daily work. Here we present a system to help users monitoring and examining their sitting behavior. The Virtual-Spine Platform (VSP) is an integrated system consisting of a real-time body position monitoring module and a data visualization module to provide individualized, immediate, and accurate sitting behavior support. It provides a comprehensive spine movement analysis as well as accumulated data visualization to demonstrate behavior patterns within a certain period. The two modules are discussed in detail focusing on the design of the VSP system with adequate capacity for continuous monitoring and a web-based interactive data analysis method to visualize and compare the sitting behavior of different persons. The data was collected in an experiment with a small group of subjects. Using this method, the behavior of five subjects was evaluated over a working day, enabling inferences and suggestions for sitting improvements. The results from the accumulated data module were used to elucidate the basic function of body position recognition of the VSP. Finally, an expert user study was conducted to evaluate VSP and support future developments.

META-pipe Authorization service

We describe the design, implementation, and use of the META-pipe Authorization service. META-pipe is a complete workflow for the analysis of marine metagenomics data. We will provide META-pipe as a web based data analysis service for ELIXIR users. We have integrated our Authorization service with the ELIXIR Authorization and Authentication Infrastructure (AAI) that allows single sign-on to services across the ELIXIR infrastructure. We use the Authorization service to authorize access to data on the META-pipe storage system and jobs in the META-pipe job queue. Our Authorization server was among the first services that integrated with ELIXIR AAI. The code is open source at: https://gitlab.com/uit-sfb/AuthService2.

Recruiting Women to a Mobile Health Smoking Cessation Trial: Low- and No-Cost Strategies.

BackgroundSuccessful recruitment of participants to mobile health (mHealth) studies presents unique challenges over in-person studies. It is important to identify recruitment strategies that maximize the limited recruitment resources available to researchers.ObjectiveThe objective of this study was to describe a case study of a unique recruitment process used in a recent mHealth software app designed to increase smoking cessation among weight-concerned women smokers. The See Me Smoke-Free app was deployed to the Google Play Store (Alphabet, Inc., Google, LLC), where potential participants could download the app and enroll in the study. Users were invited in-app to participate in the study, with no in-person contact. The recruitment activities relied primarily on earned (free) and social media.MethodsTo determine the relationship between recruitment activities and participant enrollment, the researchers explored trends in earned and social media activity in relation to app installations, examined social media messaging in relation to reach or impressions, and described app users’ self-reported referral source. The researchers collected and descriptively analyzed data regarding recruitment activities, social media audience, and app use during the 18-week recruitment period (March 30, 2015-July 31, 2015). Data were collected and aggregated from internal staff activity tracking documents and from Web-based data analytics software such as SumAll, Facebook Insights (Facebook, Inc.), and Google Analytics (Alphabet, Inc., Google, LLC).ResultsMedia coverage was documented across 75 publications and radio or television broadcasts, 35 of which were local, 39 national, and 1 international. The research team made 30 Facebook posts and 49 tweets, yielding 1821 reaches and 6336 impressions, respectively. From March 30, 2015 to July 31, 2015, 289 unique users downloaded the app, and 151 participants enrolled in the study.ConclusionsResearch identifying effective online recruitment methods for mHealth studies remains minimal, and findings are inconsistent. We demonstrated how earned media can be leveraged to recruit women to an mHealth smoking cessation trial at low cost. Using earned media and leveraging social media allowed us to enroll 3 times the number of participants that we anticipated enrolling. The cost of earned media resides in the staff time required to manage it, particularly the regular interaction with social media. We recommend communication and cooperation with university public affairs and social media offices, as well as affiliate programs in journalism and communications, so that earned media can be used as a recruitment strategy for mHealth behavior change interventions. However, press releases are not always picked up by the media and should not be considered as a stand-alone method of recruitment. Careful consideration of an intervention’s broad appeal and how that translates into potential media interest is needed when including earned media as part of a comprehensive recruitment plan for mHealth research.