scholarly journals Managing a Community Data Collection with Open Source Software

2020 ◽  
Author(s):  
Roland Schweitzer ◽  
Ethan Davis ◽  
Sean Arms ◽  
Robert Simons ◽  
Kevin O'Brien ◽  
...  
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Open Source Software ◽  
Community Data

scholarly journals WEB MAPPING ARCHITECTURES BASED ON OPEN SPECIFICATIONS AND FREE AND OPEN SOURCE SOFTWARE IN THE WATER DOMAIN

2017 ◽  
Vol IV-2/W4 ◽  
pp. 23-30
Author(s):  
C. Arias Muñoz ◽  
M. A. Brovelli ◽  
C. E. Kilsedar ◽  
R. Moreno-Sanchez ◽  
D. Oxoli
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Open Source Software ◽  
Data Availability ◽  
End User ◽  
Web Based ◽  
Web Mapping ◽  
Related Data ◽  
Data Formats ◽  
Information Assets

The availability of water-related data and information across different geographical and jurisdictional scales is of critical importance for the conservation and management of water resources in the 21<sup>st</sup> century. Today information assets are often found fragmented across multiple agencies that use incompatible data formats and procedures for data collection, storage, maintenance, analysis, and distribution. The growing adoption of Web mapping systems in the water domain is reducing the gap between data availability and its practical use and accessibility. Nevertheless, more attention must be given to the design and development of these systems to achieve high levels of interoperability and usability while fulfilling different end user informational needs. This paper first presents a brief overview of technologies used in the water domain, and then presents three examples of Web mapping architectures based on free and open source software (FOSS) and the use of open specifications (OS) that address different users’ needs for data sharing, visualization, manipulation, scenario simulations, and map production. The purpose of the paper is to illustrate how the latest developments in OS for geospatial and water-related data collection, storage, and sharing, combined with the use of mature FOSS projects facilitate the creation of sophisticated interoperable Web-based information systems in the water domain.

scholarly journals Open-source software for mouse-tracking in Qualtrics to measure category competition

2018 ◽  
Author(s):  
Maya B Mathur ◽  
David Reichling
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Real Time ◽  
Cognitive Processes ◽  
Open Source Software ◽  
Online Survey ◽  
Mouse Tracking ◽  
Crowdsourced Data ◽  
Programming Skills ◽  
User Friendly

Mouse-tracking is a sophisticated tool for measuring rapid, dynamic cognitive processes in real time, particularly in experiments investigating competition between perceptual or cognitive categories. We provide user-friendly, open-source software (https://osf.io/st2ef/) for designing and analyzing such experiments online using the Qualtrics survey platform. The software consists of a Qualtrics template with embedded Javascript and CSS along with R code to clean, parse, and analyze the data. No special programming skills are required to use this software. As we discuss, this software could be readily modified for use with other online survey platforms that allow the addition of custom Javascript. We empirically validate the provided software by benchmarking its performance on previously tested stimuli in a standard category-competition experiment with realistic crowdsourced data collection.

scholarly journals GUI ベースの web 実験作成ツール(lab.js)の紹介と実践

2020 ◽  
Author(s):  
Takayuki Osugi ◽  
Masanori Kobayashi
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Open Source Software ◽  
Laboratory Data ◽  
Practical Experiment ◽  
The University ◽  
Visual Interface

lab.js Builder is free and open-source software that makes it easy to build experiments and surveys for both online and in-laboratory data collection. By using its visual interface, stimuli can be designed and integrated into experiments and surveys without programming, though it can be also customized using HTML, CSS, and JavaScript code. This software would be beneficial for many students and scientists to build and run their experiments and surveys under the situations of homeschooling and remote working. In this tutorial article, we introduce the functions of lab.js Builder and easy-to-use method for it, and also demonstrate the method of building and conducting the practical experiment at the class of the university.

scholarly journals Modular designed Apps – an opportunity to standardize data collection methods and to encourage the reuse of software

2021 ◽  
Author(s):  
Sina C. Truckenbrodt ◽  
Maximilian Enderling ◽  
Carsten Pathe ◽  
Erik Borg ◽  
Christiane C. Schmullius ◽  
...  
Keyword(s):  
Data Collection ◽  
Data Quality ◽  
Open Source ◽  
Open Source Software ◽  
Research Question ◽  
Arable Land ◽  
Forest Monitoring ◽  
Data Collection Methods ◽  
Collection Methods ◽  
Quality Recording

&lt;p&gt;Data collection strategies vary among different citizen science projects. This complicates the intercomparability of parameter values acquired in different studies (e.g., methodological and scale issues) and results in variable data quality. This creates problems regarding the merging of different data sets and hampers the reuse of data from different projects. Modular designed applications for mobile devices (Apps) represent a framework that helps to foster the standardisation of data collection methods. While they encourage the reuse of the software, they provide enough flexibility for an adjustment in accordance with the research question(s) of interest.&lt;/p&gt;&lt;p&gt;The currently developed App &amp;#8220;FieldMApp&amp;#8221; offers such a framework running under Android and iOS. The related concept includes predefined frame functionalities, like settings for the user account and the user interface, and adaptable application-related functionalities. The latter comprise several modules that are categorized as sensor test, basic functionality, parameter collection and data quality collection modules. The interdependencies of these modules are documented in a wiki. This enables an individual and context-based selection of functionalities. The FieldMApp is based on open-source software libraries (Xamarin, Open Development Kit (ODK), SQLite, CoreCLR-NCalc, LusoV.YamarinUsbSerialForAndroid, Newtonsoft.Json, SharpZipLib) and will be published as open-source software. Hence, the existing catalogue of functionalities can be augmented in the future. The premise for such extensions is that modules are published together with smart, universally applicable data quality recording routines and a proper documentation in the wiki.&lt;/p&gt;&lt;p&gt;In this contribution, we present the concept and the structure of the FieldMApp and some current fields of application that are related to the cultivation of arable land, soil mapping, forest monitoring, and Earth Observation. The extension of the functionality catalogue is exemplified by the newly implemented speech recognition module. A related quality recording routine will be introduced. With this contribution we would like to encourage citizens and scientists to elicit which requirements such an App should fulfil from their point of view.&lt;/p&gt;

scholarly journals taxize: taxonomic search and retrieval in R

F1000Research ◽  
2013 ◽  
Vol 2 ◽  
pp. 191 ◽  
Author(s):  
Scott A. Chamberlain ◽  
Eduard Szöcs
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Open Source Software ◽  
Software Package ◽  
Data Sources ◽  
R Language ◽  
Open Source Software Package ◽  
Programmatic Access ◽  
The Web ◽  
Search And Retrieval

All species are hierarchically related to one another, and we use taxonomic names to label the nodes in this hierarchy. Taxonomic data is becoming increasingly available on the web, but scientists need a way to access it in a programmatic fashion that’s easy and reproducible. We have developed taxize, an open-source software package (freely available from http://cran.r-project.org/web/packages/taxize/index.html) for the R language. taxize provides simple, programmatic access to taxonomic data for 13 data sources around the web. We discuss the need for a taxonomic toolbelt in R, and outline a suite of use cases for which taxize is ideally suited (including a full workflow as an appendix). The taxize package facilitates open and reproducible science by allowing taxonomic data collection to be done in the open-source R platform.

Motives and Methods for Quantitative FLOSS Research

2011 ◽  
pp. 282-293
Author(s):  
Megan Conklin
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Survey Data ◽  
Open Source Software ◽  
Quantitative Data ◽  
State Of The Art ◽  
Current State ◽  
The Future ◽  
Small Project

This chapter explores the motivations and methods for mining (collecting, aggregating, distributing, and analyzing) data about free/libre open source software (FLOSS) projects. It first explores why there is a need for this type of data. Then the chapter outlines the current state-of-the art in collecting and using quantitative data about FLOSS project, focusing especially on the three main types of FLOSS data that have been gathered to date: data from large forges, data from small project sets, and survey data. Finally, the chapter will describe some possible areas for improvement and recommendations for the future of FLOSS data collection.

scholarly journals Analytics and Privacy

2020 ◽  
Vol 39 (3) ◽  
Author(s):  
Denise Quintel ◽  
Robert Wilson
Keyword(s):  
Data Collection ◽  
Open Source ◽  
Open Source Software ◽  
Academic Libraries ◽  
Data Analytics ◽  
Web Analytics ◽  
User Privacy ◽  
Software Application ◽  
Discovery Service

When selecting a web analytics tool, academic libraries have traditionally turned to Google Analytics for data collection to gain insights into the usage of their web properties. As the valuable field of data analytics continues to grow, concerns about user privacy rise as well, especially when discussing a technology giant like Google. In this article, the authors explore the feasibility of using Matomo, a free and open-source software application, for web analytics in their library’s discovery layer. Matomo is a web analytics platform designed around user-privacy assurances. This article details the installation process, makes comparisons between Matomo and Google Analytics, and describes how an open-source analytics platform works within a library-specific application, EBSCO’s Discovery Service.

scholarly journals The Essential Role of Open Data and Software for the Future of Ultrasound-Based Neuronavigation

2021 ◽  
Vol 10 ◽  
Author(s):  
Ingerid Reinertsen ◽  
D. Louis Collins ◽  
Simon Drouin
Keyword(s):  
Machine Learning ◽  
Data Collection ◽  
Open Source ◽  
Open Source Software ◽  
Graphics Processing Units ◽  
Large Scale ◽  
Training Data ◽  
Standard Format ◽  
Real Time Processing ◽  
The Impact

With the recent developments in machine learning and modern graphics processing units (GPUs), there is a marked shift in the way intra-operative ultrasound (iUS) images can be processed and presented during surgery. Real-time processing of images to highlight important anatomical structures combined with in-situ display, has the potential to greatly facilitate the acquisition and interpretation of iUS images when guiding an operation. In order to take full advantage of the recent advances in machine learning, large amounts of high-quality annotated training data are necessary to develop and validate the algorithms. To ensure efficient collection of a sufficient number of patient images and external validity of the models, training data should be collected at several centers by different neurosurgeons, and stored in a standard format directly compatible with the most commonly used machine learning toolkits and libraries. In this paper, we argue that such effort to collect and organize large-scale multi-center datasets should be based on common open source software and databases. We first describe the development of existing open-source ultrasound based neuronavigation systems and how these systems have contributed to enhanced neurosurgical guidance over the last 15 years. We review the impact of the large number of projects worldwide that have benefited from the publicly available datasets “Brain Images of Tumors for Evaluation” (BITE) and “Retrospective evaluation of Cerebral Tumors” (RESECT) that include MR and US data from brain tumor cases. We also describe the need for continuous data collection and how this effort can be organized through the use of a well-adapted and user-friendly open-source software platform that integrates both continually improved guidance and automated data collection functionalities.

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