Investigation of various data analysis techniques to identify change prone parts of an open source software

2017 ◽  
Vol 9 (2) ◽  
pp. 401-426
Author(s):  
Ruchika Malhotra ◽  
Ankita Bansal
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Analysis Techniques

scholarly journals Open Plot Project: an open-source toolkit for 3-D structural data analysis

Solid Earth ◽  
2011 ◽  
Vol 2 (1) ◽  
pp. 53-63 ◽  
Author(s):  
S. Tavani ◽  
P. Arbues ◽  
M. Snidero ◽  
N. Carrera ◽  
J. A. Muñoz
Keyword(s):  
Spatial Distribution ◽  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Source Code ◽  
Structural Data ◽  
Geological Modelling ◽  
Analysis Tools ◽  
Transect Analysis ◽  
Selection Of

Abstract. In this work we present the Open Plot Project, an open-source software for structural data analysis, including a 3-D environment. The software includes many classical functionalities of structural data analysis tools, like stereoplot, contouring, tensorial regression, scatterplots, histograms and transect analysis. In addition, efficient filtering tools are present allowing the selection of data according to their attributes, including spatial distribution and orientation. This first alpha release represents a stand-alone toolkit for structural data analysis. The presence of a 3-D environment with digitalising tools allows the integration of structural data with information extracted from georeferenced images to produce structurally validated dip domains. This, coupled with many import/export facilities, allows easy incorporation of structural analyses in workflows for 3-D geological modelling. Accordingly, Open Plot Project also candidates as a structural add-on for 3-D geological modelling software. The software (for both Windows and Linux O.S.), the User Manual, a set of example movies (complementary to the User Manual), and the source code are provided as Supplement. We intend the publication of the source code to set the foundation for free, public software that, hopefully, the structural geologists' community will use, modify, and implement. The creation of additional public controls/tools is strongly encouraged.

Conquery: an Open Source Application to analyze High Content Healthcare Data (Preprint)

2021 ◽  
Author(s):  
Fabian Kovacs ◽  
Max Thonagel ◽  
Marion Ludwig ◽  
Alexander Albrecht ◽  
Manuel Hegner ◽  
...  
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Medical Records ◽  
Healthcare Sector ◽  
Study Cohort ◽  
Decision Making Processes ◽  
Analytical Approaches

BACKGROUND Big data in healthcare must be exploited to achieve a substantial increase in efficiency and competitiveness. Especially the analysis of patient-related data possesses huge potential to improve decision-making processes. However, most analytical approaches used today are highly time- and resource-consuming. OBJECTIVE The presented software solution Conquery is an open-source software tool providing advanced, but intuitive data analysis without the need for specialized statistical training. Conquery aims to simplify big data analysis for novice database users in the medical sector. METHODS Conquery is a document-oriented distributed timeseries database and analysis platform. Its main application is the analysis of per-person medical records by non-technical medical professionals. Complex analyses are realized in the Conquery frontend by dragging tree nodes into the query editor. Queries are evaluated by a bespoke distributed query-engine for medical records in a column-oriented fashion. We present a custom compression scheme to facilitate low response times that uses online calculated as well as precomputed metadata and data statistics. RESULTS Conquery allows for easy navigation through the hierarchy and enables complex study cohort construction whilst reducing the demand on time and resources. The UI of Conquery and a query output is exemplified by the construction of a relevant clinical cohort. CONCLUSIONS Conquery is an efficient and intuitive open-source software for performant and secure data analysis and aims at supporting decision-making processes in the healthcare sector.

scholarly journals NOESIS: A Framework for Complex Network Data Analysis

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Víctor Martínez ◽  
Fernando Berzal ◽  
Juan-Carlos Cubero
Keyword(s):  
Data Mining ◽  
Open Source ◽  
Complex Network ◽  
Open Source Software ◽  
Network Data ◽  
Analysis Techniques ◽  
Software Analysis ◽  
Open Source Framework ◽  
Network Properties ◽  
Real World Problems

Network data mining has attracted a lot of attention since a large number of real-world problems have to deal with complex network data. In this paper, we present NOESIS, an open-source framework for network-based data mining. NOESIS features a large number of techniques and methods for the analysis of structural network properties, network visualization, community detection, link scoring, and link prediction. The proposed framework has been designed following solid design principles and exploits parallel computing using structured parallel programming. NOESIS also provides a stand-alone graphical user interface allowing the use of advanced software analysis techniques to users without prior programming experience. This framework is available under a BSD open-source software license.

scholarly journals Takin: An open-source software for experiment planning, visualisation, and data analysis

SoftwareX ◽  
2016 ◽  
Vol 5 ◽  
pp. 121-126 ◽  
Author(s):  
Tobias Weber ◽  
Robert Georgii ◽  
Peter Böni
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Experiment Planning

scholarly journals Integrated open-source software for multiscale electrophysiology

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Konstantinos Nasiotis ◽  
Martin Cousineau ◽  
François Tadel ◽  
Adrien Peyrache ◽  
Richard M. Leahy ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Analysis Data ◽  
Open Science ◽  
Dense Array ◽  
Unrestricted Access ◽  
Research Transparency ◽  
Programming Skills ◽  
User Friendly

Abstract The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results. Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology.

The MetaProteomeAnalyzer: A Powerful Open-Source Software Suite for Metaproteomics Data Analysis and Interpretation

2015 ◽  
Vol 14 (3) ◽  
pp. 1557-1565 ◽  
Author(s):  
Thilo Muth ◽  
Alexander Behne ◽  
Robert Heyer ◽  
Fabian Kohrs ◽  
Dirk Benndorf ◽  
...  
Keyword(s):  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Software Suite

scholarly journals Electron Microscopy (Big and Small) Data Analysis With the Open Source Software Package HyperSpy

2017 ◽  
Vol 23 (S1) ◽  
pp. 214-215 ◽  
Author(s):  
Francisco de la Pena ◽  
Tomas Ostasevicius ◽  
Vidar Tonaas Fauske ◽  
Pierre Burdet ◽  
Petras Jokubauskas ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Software Package ◽  
Small Data ◽  
Open Source Software Package

scholarly journals Program R: applications in plant breeding

2011 ◽  
Vol 11 (spe) ◽  
pp. 91-92 ◽  
Author(s):  
Luiz Alexandre Peternelli
Keyword(s):  
Data Analysis ◽  
Plant Breeding ◽  
Open Source ◽  
Open Source Software ◽  
Public Domain ◽  
Statistical Analyses ◽  
Statistical Procedures ◽  
Statistical Program ◽  
Public Domain Software ◽  
Default Setting

Nowadays the demand for so-called free, or open source software for data analysis as well as the appeal to use it is great. An public domain software that has become extremely well-known, with ever-increasing numbers of fans and even co-workers, is Environment R, or simply R. R is extremely useful for data analysis and manipulation in view of a range of tools already implemented. Also, R is not simply a statistical program, because, by its easy on using internal functions and also creating new ones, statistical procedures applied to data can also be created, manipulated, evaluated and interpreted. R contains numerous libraries (or packages), some already included in the default setting. This course will focus on the application of R in statistical analyses in plant breeding. Explanations on the use of various commands and functions will be illustrated with examples, to facilitate the interpretation and adaptation to other similar problems.

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