scholarly journals Impact of the persistence layer implementation methods on application per-formance

2020 ◽  
Vol 17 ◽  
pp. 326-331
Author(s):  
Kamil Siebyła ◽  
Maria Skublewska-Paszkowska
Keyword(s):  
Response Time ◽  
Web Applications ◽  
Application Programming Interface ◽  
Data Access ◽  
Persistence Layer ◽  
Application Programming ◽  
Different Levels ◽  
Programming Interface ◽  
The Way

There are various methods for creating web applications. Each of these methods has different levels of performance. This factor is measurable at every level of the application. The performance of the frontend layer depends on the response time from individual endpoint of the used API (Application Programming Interface). The way the data access will be programmed at a specific endpoint, therefore, determines the performance of the entire application. There are many programming methods that are often time-consuming to implement. This article presents a comparison of the available methods of handling the persistence layer in relation to the efficiency of their implementation.                                                                                    

User identification across online social networks in practice: Pitfalls and solutions

2016 ◽  
Vol 44 (3) ◽  
pp. 377-391 ◽  
Author(s):  
Azadeh Esfandyari ◽  
Matteo Zignani ◽  
Sabrina Gaito ◽  
Gian Paolo Rossi
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Full Range ◽  
Application Programming Interface ◽  
User Identification ◽  
Application Programming ◽  
Test Sets ◽  
Set Up ◽  
Different Levels ◽  
Programming Interface

To take advantage of the full range of services that online social networks (OSNs) offer, people commonly open several accounts on diverse OSNs where they leave lots of different types of profile information. The integration of these pieces of information from various sources can be achieved by identifying individuals across social networks. In this article, we address the problem of user identification by treating it as a classification task. Relying on common public attributes available through the official application programming interface (API) of social networks, we propose different methods for building negative instances that go beyond usual random selection so as to investigate the effectiveness of each method in training the classifier. Two test sets with different levels of discrimination are set up to evaluate the robustness of our different classifiers. The effectiveness of the approach is measured in real conditions by matching profiles gathered from Google+, Facebook and Twitter.

Studying Facebook and Instagram data: The Digital Footprints software

First Monday ◽  
2015 ◽  
Author(s):  
Anja Bechmann ◽  
Peter Bjerregaard Vahlstrup
Keyword(s):  
Data Extraction ◽  
Application Programming Interface ◽  
Data Access ◽  
Quality Data ◽  
Ethical Considerations ◽  
Private Data ◽  
User Data ◽  
Application Programming ◽  
Digital Footprints ◽  
Programming Interface

The aim of this article is to discuss methodological implications and challenges in different kinds of deep and big data studies of Facebook and Instagram through methods involving the use of Application Programming Interface (API) data. This article describes and discusses Digital Footprints (www.digitalfootprints.dk), a data extraction and analytics software that allows researchers to extract user data from Facebook and Instagram data sources; public streams as well as private data with user consent. Based on insights from the software design process and data driven studies the article argues for three main challenges: Data quality, data access and analysis, and legal and ethical considerations.

scholarly journals Push Button Population Health: The SMART/HL7 FHIR Bulk Data Access Application Programming Interface

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Kenneth D. Mandl ◽  
Daniel Gottlieb ◽  
Joshua C. Mandel ◽  
Vladimir Ignatov ◽  
Raheel Sayeed ◽  
...  
Keyword(s):  
Information Technology ◽  
Application Programming Interface ◽  
Data Access ◽  
Push Button ◽  
Hl7 Fhir ◽  
Bulk Data ◽  
Application Programming ◽  
Data Elements ◽  
21St Century Cures Act ◽  
Programming Interface

AbstractThe 21st Century Cures Act requires that certified health information technology have an application programming interface (API) giving access to all data elements of a patient’s electronic health record, “without special effort”. In the spring of 2020, the Office of the National Coordinator of Health Information Technology (ONC) published a rule—21st Century Cures Act Interoperability, Information Blocking, and the ONC Health IT Certification Program—regulating the API requirement along with protections against information blocking. The rule specifies the SMART/HL7 FHIR Bulk Data Access API, which enables access to patient-level data across a patient population, supporting myriad use cases across healthcare, research, and public health ecosystems. The API enables “push button population health” in that core data elements can readily and standardly be extracted from electronic health records, enabling local, regional, and national-scale data-driven innovation.

scholarly journals Efficient application programming interface for multi-dimensional modeling data

2011 ◽  
Vol 14 (1) ◽  
pp. 1-12
Author(s):  
Norman L. Jones ◽  
Robert M. Wallace ◽  
Russell Jones ◽  
Cary Butler ◽  
Alan Zundel
Keyword(s):  
Data Sharing ◽  
Cross Sections ◽  
Computational Models ◽  
Application Programming Interface ◽  
Data Access ◽  
Brigham Young University ◽  
Us Army ◽  
Data Standard ◽  
Application Programming ◽  
Programming Interface

This paper describes an Application Programming Interface (API) for managing multi-dimensional data produced for water resource computational modeling that is being developed by the US Army Engineer Research and Development Center (ERDC), in conjunction with Brigham Young University. This API, along with a corresponding data standard, is being implemented within ERDC computational models to facilitate rapid data access, enhanced data compression and data sharing, and cross-platform independence. The API and data standard are known as the eXtensible Model Data Format (XMDF), and version 1.3 is available for free download. This API is designed to manage geometric data associated with grids, meshes, riverine and coastal cross sections, and both static and transient array-based datasets. The inclusion of coordinate system data makes it possible to share data between models developed in different coordinate systems. XMDF is used to store the data-intensive components of a modeling study in a compressed binary format that is platform-independent. It also provides a standardized file format that enhances modeling linking and data sharing between models.

VirES for Aeolus - Virtual Research Environment (VRE)

2021 ◽  
Author(s):  
Daniel Santillan Pedrosa ◽  
Alexander Geiss ◽  
Isabell Krisch ◽  
Fabian Weiler ◽  
Peggy Fischer ◽  
...  
Keyword(s):  
Application Programming Interface ◽  
Data Access ◽  
Easy Access ◽  
Research Environment ◽  
Web Browser ◽  
Explorer Mission ◽  
Virtual Research Environment ◽  
Application Programming ◽  
Open Service ◽  
Programming Interface

<p><span>The VirES for Aeolus service (https://aeolus.services) has been successfully running </span><span>by EOX </span><span>since August 2018. The service </span><span>provides</span><span> easy access </span><span>and</span><span> analysis functions for the entire data archive of ESA's Aeolus Earth Explorer mission </span><span>through a web browser</span><span>.</span></p><p><span>This </span>free and open service <span>is being extended with a Virtual Research Environment (VRE). </span><span>The VRE </span><span>builds on the available data access capabilities of the service and provides </span><span>a </span><span>data access Application Programming Interface (API) a</span><span>s part of a </span><span>developing environment </span><span>i</span><span>n the cloud </span><span>using </span><span>JupyterHub and </span><span>JupyterLab</span><span> for processing and exploitation of the Aeolus data. </span>In collaboration with Aeolus DISC user requirements are being collected, implemented and validated.</p><p>Jupyter Notebook templates, an extensive set of tutorials, and documentation are being made available to enable a quick start on how to use VRE in projects. <span>The VRE is intended to support and simplify </span><span>the </span><span>work of (citizen-) scientists </span><span>interested in</span><span> Aeolus data by being able to </span><span>quickly develop processes or algorithms that can be </span><span>shar</span><span>ed or used to create </span><span>visualizations</span><span> for publications. Having a unified constant platform could potentially also be very helpful for calibration and validation activities </span><span>by </span><span>allowing easier result comparisons. </span></p>

scholarly journals Lessons Learned about FOLIO’s APIs

2021 ◽  
Vol 6 (2) ◽  
pp. 30-39
Author(s):  
Guy Dobson
Keyword(s):  
User Interface ◽  
Web Applications ◽  
Application Programming Interface ◽  
Building Blocks ◽  
Lessons Learned ◽  
Library Services ◽  
Library System ◽  
Application Programming ◽  
Programming Interface

APIs (Application Programming Interface) provide the ability to do what needs to be done. The fact that FOLIO includes API as one of its building blocks makes it that much more attractive. When my library’s administration decided to switch from a legacy ILS (Integrated Library System) to a FOLIO LSP (Library Services Platform) the first thing that I looked at was the API. The lessons learned helped me to configure the system and massage the data from ILS output to FOLIO-friendly input. By building web applications and writing Perl scripts our staff is able to get the job done even when it is impossible to accomplish the task through the user interface (UI).

scholarly journals Neuroimaging Data Access and Query through a Common Application Programming Interface

2014 ◽  
Vol 8 ◽  
Author(s):  
Nichols B. Nolan ◽  
Haselgrove Christian ◽  
Poline Jean-Baptiste ◽  
Ghosh Satrajit S.
Keyword(s):  
Application Programming Interface ◽  
Data Access ◽  
Neuroimaging Data ◽  
Application Programming ◽  
Common Application ◽  
Programming Interface

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).

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