scholarly journals NASA GeneLab: interfaces for the exploration of space omics data

2020 ◽  
Vol 49 (D1) ◽  
pp. D1515-D1522 ◽  
Author(s):  
Daniel C Berrios ◽  
Jonathan Galazka ◽  
Kirill Grigorev ◽  
Samrawit Gebre ◽  
Sylvain V Costes
Keyword(s):  
Data Entry ◽  
Application Programming Interface ◽  
Data Repository ◽  
Omics Data ◽  
Online Data ◽  
Support Tools ◽  
Working Groups ◽  
Student Training ◽  
Application Programming ◽  
Space Environments

Abstract The mission of NASA’s GeneLab database (https://genelab.nasa.gov/) is to collect, curate, and provide access to the genomic, transcriptomic, proteomic and metabolomic (so-called ‘omics’) data from biospecimens flown in space or exposed to simulated space stressors, maximizing their utilization. This large collection of data enables the exploration of molecular network responses to space environments using a systems biology approach. We review here the various components of the GeneLab platform, including the new data repository web interface, and the GeneLab Online Data Entry (GEODE) web portal, which will support the expansion of the database in the future to include companion non-omics assay data. We discuss our design for GEODE, particularly how it promotes investigators providing more accurate metadata, reducing the curation effort required of GeneLab staff. We also introduce here a new GeneLab Application Programming Interface (API) specifically designed to support tools for the visualization of processed omics data. We review the outreach efforts by GeneLab to utilize the spaceflight data in the repository to generate novel discoveries and develop new hypotheses, including spearheading data analysis working groups, and a high school student training program. All these efforts are aimed ultimately at supporting precision risk management for human space exploration.

scholarly journals Use and users of the Minrva mobile app

2017 ◽  
Vol 45 (3) ◽  
pp. 472-484 ◽  
Author(s):  
Jim Hahn
Keyword(s):  
Interface Design ◽  
Application Programming Interface ◽  
Mobile App ◽  
First Year Experience ◽  
First Year ◽  
Content Type ◽  
First Semester ◽  
Support Tools ◽  
New Students ◽  
Application Programming

Purpose The purpose of this paper is to investigate new undergraduate student library engagement in the Minrva mobile app during the months of May 2015 through December 2015. Design/methodology/approach This research investigated what parts of a mobile app new students were using in their first semester after downloading the app. The quantitative study used application programming interface log analysis to better understand what parts of the app new students use in the mobile app. Findings By undertaking this study, the author has a better understanding about what students are finding useful within the app and what tools are not being used by this cohort in their first semester. Originality/value The value of this research is in helping system designers and first-year experience planners know what mobile support tools students are finding useful in their first semester. Implication for mobile interface design based on module popularity are discussed.

scholarly journals Streamlining statistical reproducibility: NHLBI ORCHID clinical trial results reproduction

JAMIA Open ◽  
2022 ◽  
Vol 5 (1) ◽  
Author(s):  
Arnaud Serret-Larmande ◽  
Jonathan R Kaltman ◽  
Paul Avillach
Keyword(s):  
Clinical Trial ◽  
Peer Review Process ◽  
Application Programming Interface ◽  
Data Repository ◽  
Practical Implementation ◽  
Media Audiences ◽  
Blood Institute ◽  
National Heart Lung ◽  
Application Programming ◽  
Clinical Trial Results

Abstract Reproducibility in medical research has been a long-standing issue. More recently, the COVID-19 pandemic has publicly underlined this fact as the retraction of several studies reached out to general media audiences. A significant number of these retractions occurred after in-depth scrutiny of the methodology and results by the scientific community. Consequently, these retractions have undermined confidence in the peer-review process, which is not considered sufficiently reliable to generate trust in the published results. This partly stems from opacity in published results, the practical implementation of the statistical analysis often remaining undisclosed. We present a workflow that uses a combination of informatics tools to foster statistical reproducibility: an open-source programming language, Jupyter Notebook, cloud-based data repository, and an application programming interface can streamline an analysis and help to kick-start new analyses. We illustrate this principle by (1) reproducing the results of the ORCHID clinical trial, which evaluated the efficacy of hydroxychloroquine in COVID-19 patients, and (2) expanding on the analyses conducted in the original trial by investigating the association of premedication with biological laboratory results. Such workflows will be encouraged for future publications from National Heart, Lung, and Blood Institute-funded studies.

Development and commissioning of decision support tools for sewerage management

2006 ◽  
Vol 53 (4-5) ◽  
pp. 293-302 ◽  
Author(s):  
G. Manic ◽  
C. Printemps ◽  
M. Zug ◽  
C. Lemoine
Keyword(s):  
Decision Support ◽  
Wastewater Treatment Plants ◽  
Application Programming Interface ◽  
Decision Support Tools ◽  
Network Systems ◽  
Applied Software ◽  
Support Tools ◽  
First Results ◽  
Application Programming ◽  
The One

Managing sewerage systems is a highly complex task due to the dynamic nature of the facilities. Their performance strongly depends on the know-how applied by the operators. In order to define optimal operational settings, two decision support tools based on mathematical models have been developed. Moreover, easy-to-use interfaces have been created as well, aiding operators who presumably do not have the necessary skills to use modelling software. The two developed programs simulate the behaviour of both wastewater treatment plants (WWTP) and sewer network systems, respectively. They have essentially the same structure, including raw data management and statistical analysis, a simulation layer using the application programming interface of the applied software and a layer responsible for the representation of the obtained results. Four user modes are provided in the two software including the simulation of historical data using the applied and novel operational settings, as well as modes concerning prediction of possible operation periods and updates. Concerning the WWTP software, it was successfully installed in Nantes (France) in June 2004. Moreover, the one managing sewer networks has been deployed in Saint-Malo (France) in January 2005. This paper presents the structure of the developed software and the first results obtained during the commissioning phase.

scholarly journals AquaCropR: Crop Growth Model for R

Agronomy ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 378 ◽  
Author(s):  
Rodriguez ◽  
Ober
Keyword(s):  
Application Programming Interface ◽  
Triticum Aestivum L ◽  
Crop Species ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Aquacrop Model ◽  
Support Tools ◽  
Application Programming ◽  
Multiple Scenarios ◽  
Programming Interface

The Food and Agriculture Organization (FAO) AquaCrop model, run either via a standalone graphical user interface (GUI) or via a matlab application programming interface (API) (AquaCrop-OS), has been successfully tested on many crop species and under multiple scenarios. However, with these current versions, it is difficult for users to adapt formulae, add functionality or incorporate the model into other applications such as decision support tools. Here, we report on the release of a version of AquaCrop written in R. Performance of the model was tested using published datasets of wheat (Triticum aestivum L.) and maize (Zea mays L.), comparing output from AquaCropR with these other versions of AquaCrop. Our goal in developing this version was to widen the use and improvement of AquaCrop through open access.

scholarly journals Facilitating API lookup for novices learning data wrangling using thumbnail graphics

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Lovisa Sundin ◽  
Nourhan Sakr ◽  
Juho Leinonen ◽  
Quintin Cutts
Keyword(s):  
Data Science ◽  
Application Programming Interface ◽  
Online Data ◽  
Negative Results ◽  
Application Programming ◽  
And Performance ◽  
Learner Activity ◽  
Programming Interface ◽  
Learning Data

<p style='text-indent:20px;'>With the rising demand for data science skills, the ability to wrangle data programmatically becomes a crucial barrier. In this paper, we discuss the centrality of API (application programming interface) lookup to data wrangling, and how an ontology-structured command menu could facilitate it. We design thumbnail graphics as visual alternatives to explaining data wrangling operations and use a survey to validate their quality. We furthermore predict that thumbnail graphics make the menu more navigable, improving lookup efficiency and performance. Our predictions are tested using Slice N Dice, an online data wrangling tutorial platform that collects learner activity. It includes both non-programmatic and programmatic data wrangling exercises. Participants from a multi-institutional sample (<i>n</i> = 200) were randomly assigned the tutorial either with or without thumbnail graphics. Our results show that thumbnail graphics reduce the need for clarifications, thereby assisting API lookup for novices learning data wrangling. We further present some negative results regarding performance gain and follow up with a discussion on why the differences are subtle and how they can be improved. Last but not least, we complement our statistical results with a qualitative study where we receive positive feedback from our participants on the design and helpfulness of the thumbnail graphics.</p>

scholarly journals TaxonWorks

2018 ◽  
Vol 2 ◽  
pp. e25560
Author(s):  
Dmitry Dmitriev
Keyword(s):  
Web Applications ◽  
Data Entry ◽  
Application Programming Interface ◽  
Database Access ◽  
Software Ecosystem ◽  
Data Share ◽  
Application Programming ◽  
User Friendly ◽  
Species Descriptions ◽  
Programming Interface

TaxonWorks (http://taxonworks.org) is an integrated workbench for taxonomists and biodiversity scientists. It is designed to capture, organize, and enrich data, share and refine it with collaborators, and package it for analysis and publication. It is based on PostgreSQL (database) and the Ruby-on-Rails programming language and framework for developing web applications (https://github.com/SpeciesFileGroup/taxonworks). The TaxonWorks community is built around an open software ecosystem that facilitates participation at many levels. TaxonWorks is designed to serve both researchers who create and curate the data, as well as technical users, such as programmers and informatics specialists, who act as data consumers. TaxonWorks provides researchers with robust, user friendly interfaces based on well thought out customized workflows for efficient and validated data entry. It provides technical users database access through an application programming interface (API) that serves data in JSON format. The data model includes coverage for nearly all classes of data recorded in modern taxonomic treatments primary studies of biodiversity, including nomenclature, bibliography, specimens and collecting events, phylogenetic matrices and species descriptions, etc. The nomenclatural classes are based on the NOMEN ontology (https://github.com/SpeciesFileGroup/nomen).

scholarly journals BloodPAC Data Commons for Liquid Biopsy Data

2021 ◽  
pp. 479-486
Author(s):  
Robert L. Grossman ◽  
Jonathan R. Dry ◽  
Sean E. Hanlon ◽  
Donald J. Johann ◽  
Anand Kolatkar ◽  
...  
Keyword(s):  
Liquid Biopsy ◽  
Scientific Evidence ◽  
Application Programming Interface ◽  
The Public ◽  
Data Platform ◽  
Working Groups ◽  
The Commons ◽  
Application Programming ◽  
Using Data ◽  
Data Commons

PURPOSE The Blood Profiling Atlas in Cancer (BloodPAC) Data Commons (BPDC) is being developed and is operated by the public-private BloodPAC Consortium to support the liquid biopsy community. It is an interoperable data commons with the ultimate aim of serving as a recognized source of valid scientific evidence for liquid biopsy assays for industry, academia, and standards and regulatory stakeholders. METHODS The BPDC is implemented using the open source Gen3 data commons platform ( https://gen3.org ). In particular, the BPDC Data Exploration Portal, BPDC Data Submission Portal, the BPDC Workspace Hub, and the BloodPAC application programming interface (API) were all automatically generated from the BloodPAC Data Model using the Gen3 data commons platform. BPDC uses Gen3's implementation of the data commons framework services so that it can interoperate through secure, compliant APIs with other data commons using data commons framework service, such as National Cancer Institute's Cancer Research Data Commons. RESULTS The BPDC contains 57 studies and projects spanning more than 4,100 cases. This amounts to 5,700 aliquots (blood plasma, serum, or a contrived sample) that have been subjected to a liquid biopsy assay, quantified, and then contributed by members of the BloodPAC Consortium. In all, there are more than 31,000 files in the commons as of December 2020. We describe the BPDC, the data it manages, the process that the BloodPAC Consortium used to develop it, and some of the applications that have been developed using its API. CONCLUSION The BPDC has been the data platform used by BloodPAC during the past 4 years to manage the data for the consortium and to provide workspaces for its working groups.

Sistem Pengawasan Aktifitas Penggunaan Smartphone Android

2018 ◽  
Vol 9 (1) ◽  
pp. 24-31
Author(s):  
Rudianto Rudianto ◽  
Eko Budi Setiawan
Keyword(s):  
Application Programming Interface ◽  
Third Party ◽  
Image Content ◽  
Image File ◽  
Application Programming ◽  
Index Terms ◽  
Programming Interface

Availability the Application Programming Interface (API) for third-party applications on Android devices provides an opportunity to monitor Android devices with each other. This is used to create an application that can facilitate parents in child supervision through Android devices owned. In this study, some features added to the classification of image content on Android devices related to negative content. In this case, researchers using Clarifai API. The result of this research is to produce a system which has feature, give a report of image file contained in target smartphone and can do deletion on the image file, receive browser history report and can directly visit in the application, receive a report of child location and can be directly contacted via this application. This application works well on the Android Lollipop (API Level 22). Index Terms— Application Programming Interface(API), Monitoring, Negative Content, Children, Parent.

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