Library Code Research Articles

High-Throughput Multiplexed Plasmonic Color Encryption of Microgel Architectures via Programmable Dithering-Mask Flow Microlithography.

Silver nanoparticles (AgNPs) are known for their unique plasmonic colors and interaction with light, making them ideal for color printing and data encoding. Traditional methods like electron beam lithography (EBL) and focused ion beam (FIB) milling, however, suffer from low throughput and high costs. In this paper, a scalable and cost-efficient method is introduced for producing multiplexed plasmonic colors by in situ photoreducing AgNPs within microgel architectures with controlled porosity. Utilizing a digital micro-mirror device (DMD)-based flow microlithography system combined with a programmable dithering-mask technique, the high-throughput synthesis of shape or barcoded microparticles is facilitated, along with large-scale, high-resolution images embedded with hidden multiplexed plasmonic colors. This approach allows for a hidden multiplexed plasmonic color code library, significant enhancing the encoding capacity of barcode microparticles from 33 to 303 (a 1000-fold increase). Additionally, quantitative agreement is achieved between chemically encrypted and optically decrypted plasmonic colors using a deep learning classifier. Moreover, the method also supports the production of large scale (>5.6 × 5.6cm2), high-resolution (>300 dpi) microgel arrays encrypted with multiple plasmonic colors in under 30min. The multiplexed plasmonic coloration strategy in microgel architectures paves a new way for hidden data storage, secure optical labeling, and anti-counterfeiting technologies.

SISTEM INFORMASI PERPUSTAKAAN MENGGUNAKAN QR CODE PADA SMP NEGERI 6 KEMPAS BERBASIS WEB

Information technology has developed very rapidly nowadays, this has had a significant influence on human activities, such as making various fields of human work easier. One of these technological developments is the Library Information System. The Library of SMP Negeri 6 Kempas currently still uses media in the form of master books as storage media to manage library data. Storage that uses master books has the potential to experience many problems such as data loss because master books are easily torn, faded or lost, inaccuracies in reports, the length of the book management process and many other problems. The aim of this research is to produce a website-based library information system using QR Codes that can be used to handle the service process and book data management at the SMP Negeri 6 Kempas library and overcome the problems and weaknesses that occur when using the old system that is currently in use. The result of this research is to produce a Web-based QR Code Library Information System and has passed system Functionality testing with a score of 100% and Usability with a score of 81.6%.

Spectral ruins: Empathy with inanimate material movements

Simulations are interactive, lively models of material events. Working with simulations that require the consideration of mass, gravity, and texture becomes an embodied experience. Much like video games, simulations imitate the physics of the material world and, as such, engage us corporeally. This dynamic between interactive model and user is particularly generative when the content of a simulation is inanimate, or inorganic materials. Digital models of static matter in motion offer the user a unique opportunity to relate to things that are typically understood as inert or nonliving. While empathy with the nonliving is a complex relationship to authentically construct, the ecological implications of this interaction are significant. This paper uses critical tools from video game studies and media theory to study simulations in experimental architecture and contemporary fine art practice. The essay posits a thesis informed by ecocriticism that users can build a tactile, bodily understanding of material behaviors by designing and interacting with tools built into animation, gaming, and visual coding platforms. A series of case-studies in art and design are examined with particular emphasis on their use of digital physics engines and code libraries that imitate natural behaviors.

StarPlat: A versatile DSL for graph analytics

Graphs model several real-world phenomena. With the growth of unstructured and semi-structured data, parallelization of graph algorithms is inevitable. Unfortunately, due to inherent irregularity of computation, memory access, and communication, graph algorithms are traditionally challenging to parallelize. To tame this challenge, several libraries, frameworks, and domain-specific languages (DSLs) have been proposed to reduce the parallel programming burden of the users, who are often domain experts. However, existing frameworks to model graph algorithms typically target a single architecture. In this paper, we present a graph DSL, named StarPlat, that allows programmers to specify graph algorithms in a high-level format, but generates code for three different backends from the same algorithmic specification. In particular, the DSL compiler generates OpenMP for multi-core systems, MPI for distributed systems, and CUDA for many-core GPUs. Since these three are completely different parallel programming paradigms, binding them together under the same language is challenging. We share our experience with the language design. Central to our compiler is an intermediate representation which allows a common representation of the high-level program, from which individual backend code generations begin. We demonstrate the expressiveness of StarPlat by specifying four graph algorithms: betweenness centrality computation, page rank computation, single-source shortest paths, and triangle counting. Using a suite of ten large graphs, we illustrate the effectiveness of our approach by comparing the performance of the generated codes with that obtained with hand-crafted library codes. We find that the generated code is competitive to library-based codes in many cases. More importantly, we show the feasibility to generate efficient codes for different target architectures from the same algorithmic specification of graph algorithms.

MPNet: A lightweight fault diagnosis network for rotating machinery

Rotating machinery is prone to faults, especially bearing faults. Existing machinery fault diagnosis methods suffer from low accuracy and poor robustness under actual complex working conditions. To address these problems, this paper proposes a sound signal-based rotating machinery fault diagnosis method and designs a lightweight fault diagnosis network called MPNet. A multi-branch feature fusion module is constructed to capture the multi-scale correlation information of the sound features. A residual attention pyramid module is designed to adaptively learn abstract fault information at different levels, then the feature-enhanced attention maps at multi-scale generated by hierarchical fusion. Experimental results on a public bearing dataset and a self-made idler dataset reveal that the proposed method achieves 95.83% and 94.81% accuracy, respectively, meeting the requirements of lightweight and real-time detection. Compared with conventional methods, the proposed method has better diagnostic precision and robustness under strong noise. The code library is available at: https://github.com/xgli411/MPNet.

Fixed Source Sensitivity Calculations for Inertial Confinement Fusion Applications

A numerical code library was developed for the radiation transport code MCNP6.3 to calculate generalized response sensitivity coefficients for fixed source neutron transport problems with applications to inertial confinement fusion (ICF) experiments. The new MCNP6.3 dependency is used to generate a novel time convolution response that represents a neutron time-of-flight (nToF) signal. The traditional suite of macroscopic cross-section sensitivities and constrained fixed source probability distribution sensitivities are available for both the standard and the new response tallies in this library. However, novel sensitivity coefficients for the constrained hyperparameters of analytic fixed source probability distributions are emphasized in this work for their connection to ICF neutron transport models. Particularly, advanced Monte Carlo methods are developed for calculating the sensitivity of a nToF signal to perturbations in an ICF plasma’s ion temperature and burn history as well as perturbations in the target liner mass density and the shape parameters of the nToF detector’s impulse response function. Together, these capabilities form an advanced suite of computational tools that can be used to analyze and extract information from any ICF experimental platform.

PhoenixMR: A GPU-based MRI simulation framework with runtime-dynamic code execution.

Simulations of physical processes and behavior can provide unique insights and understanding of real-world problems. Magnetic Resonance Imaging (MRI) is an imaging technique with several components of complexity. Several of these components have been characterized and simulated in the past. However, several computational challenges prevent simulations from being simultaneously fast, flexible, and accurate. The simulation of MRI experiments is underutilized by medical physicists and researchers using currently available simulators due to reasons including speed, accuracy, and extensibility constraints. This paper introduces an innovative MRI simulation engine and framework that aims to overcome these issues making available realistic and fast MRIsimulation. Using the CUDA C/C++ programing language, an MRI simulation engine (PhoenixMR), incorporating a Turing-complete virtual machine (VM) to simulate abstract spatiotemporal complexities, was developed. This engine solves a set of time-discrete Bloch equationsusing the symmetric operator splitting technique. An extensible front-end framework package (written in Python) aids the use of PhoenixMR to simplify simulationdevelopment. The PhoenixMR library and front-end codes have been developed and tested. A set of example simulations were performed to demonstrate the ease of use and flexibility of simulation components such as geometrical setup, pulse sequence design, phantom design, and so forth. Initial validation of PhoenixMR is performed by comparing its accuracy and performance against a widely used MRI simulator using identical simulation parameters. Validation results show PhoenixMR simulations are three orders of magnitude faster. There is also strong agreement betweenmodels. A novel MRI simulation platform called PhoenixMR has been introduced. This research tool is designed to be usable by physicists and engineers interested in performing MRI simulations. Examples are shown demonstrating the accuracy, flexibility, and usability of PhoenixMR in several key areas of MRIsimulation.

A Collaborative Code Platform with Advanced AI Features and Real-Time Collaboration Tools

Abstract: Good collaboration and code management are crucial in today's software development environment. Our research has launched a new collaborative process that combines AI resources, including AI and global research, to improve products and enhance and facilitate collaboration. The platform features real-time collaboration tools such as dynamic text with multilanguage support, dialog functionality, and notepad functionality. With OAuth authentication, users can seamlessly perform CRUD operations on files and directories, share code repositories, and participate in live coding sessions. The platform supports compilation and execution of a code file and follows good design principles such as caching, microservices architecture, and containerization to ensure scalability and performance. The platform focuses on user experience by providing simple user interface design and easy interface navigation. Users can create workspaces, share them collaboratively, and seamlessly import repositories from Git. The platform's intelligent data manager helps manage files and directories, while the collaborative platform allows developers to collaborate on code libraries efficiently. The platform is modern web-based, using React on the frontend and Node.js on the backend; Supported with syntax highlighting and smart initialization along with Socket.io for runtime with SQL and NoSQL databases. Provides comprehensive language support. All progress is saved, providing users with peace of mind. While the basic design is for desktops, future iterations are expected to support mobile devices.

A Prototype Software Framework for Transferable Computational Health Economic Models and Its Early Application in Youth Mental Health.

We are developing an economic model to explore multiple topics in Australian youth mental health policy. To help make that model more readily transferable to other jurisdictions, we developed a software framework for authoring modular computational health economic models (CHEMs) (the software files that implement health economic models). We specified framework user requirements for: a simple programming syntax; a template CHEM module; tools for authoring new CHEM modules; search tools for finding existing CHEM modules; tools for supplying CHEM modules with data; reproducible analysis and reporting tools; and tools to help maintain a CHEM project website. We implemented the framework as six development version code libraries in the programming language R that integrate with online services for software development and research data archiving. We used the framework to author five development version R libraries of CHEM modules focussed on utility mapping in youth mental health. These modules provide tools for variable validation, dataset description, multi-attribute instrument scoring, construction of mapping models, reporting of mapping studies and making out of sample predictions. We assessed these CHEM module libraries as mostly meeting transparency, reusability and updatability criteria that we have previously developed, but requiring more detailed documentation and unit testing of individual modules. Our software framework has potential value as a prototype for future tools to support the development of transferable CHEMs.Code: Visit https://www.ready4-dev.com for more information about how to find, install and apply the prototype software framework.

Managing Cyber Security Debt: Strategies for Identification, Prioritisation, and Mitigation

This paper explores cyber security debt, a technical debt arising from unaddressed security vulnerabilities in an organisation's IT systems. These vulnerabilities accumulate due to resource limitations, time constraints, and expertise gaps, potentially leading to security breaches and data compromises. The paper outlines the cyber security debt management process involving identification, prioritisation, and mitigation strategies. Drawing parallels to financial debt, the authors emphasise the escalating risks of delaying cyber security debt repayment. The paper underscores the significance of diligent debt management in maintaining digital resilience and mitigating cyber threats. The increasing interconnectedness of systems and rapid software development has given rise to a hidden challenge known as cyber security debt. Cyber security debt is posed as a subset of technical debt, encompassing the accumulation of security vulnerabilities within an organisation's IT infrastructure and applications. Drawing a parallel between cyber security debt and its financial counterpart, the authors underscore the grave risks of deferring debt repayment. Just as financial debt accrues interest, unresolved security vulnerabilities compound over time, elevating the likelihood of breaches and data exposure. A poignant case study of the Equifax breach exemplifies the real-world consequences of neglecting security debt management. The failure to patch a well-known vulnerability led to a colossal data breach, highlighting the urgency of addressing security weaknesses promptly. Complex in nature, cyber security debt materialises when organisations fail to address vulnerabilities during various operational life cycles. These vulnerabilities might remain concealed within IT architecture, legacy code, or third-party libraries, posing a formidable challenge to detection and resolution. By understanding the parallels between financial and cyber security debt and proactively managing the latter, organisations can enhance their ability to safeguard against evolving cyber threats and maintain a robust security posture.

Quantum computing library for quantum chemistry applications

Quantum computing is aimed to solve tasks, which are believed to be exponentially hard to existing computational devices and tools. A prominent example of such classically hard problems is simulating complex quantum many-body systems, in particular, for quantum chemistry. However, solving realistic quantum chemistry problems with quantum computers encounters various difficulties, which are related, first, to limited computational capabilities of existing quantum devices and, second, to the efficiency of algorithmic approaches. In the present work, we address the algorithmic side of quantum chemistry applications by introducing a Python 3 code library, whose primary objective is to speed up the development of variational quantum algorithms for electronic structure problems. We describe the various features and capabilities of this library, including its ease in constructing customized versions of variational quantum algorithms. We elucidate how the developed library allows one to design quantum circuits and enable for the efficient execution of quantum algorithms. Furthermore, the library facilitates the integration of classical and quantum algorithms for hybrid computations and helps to realize the cross-verification of data with traditional computational methods, thereby enhancing the overall reliability of quantum chemistry simulations.

The fast neutron fluence and the activation monitor activity calculations using fine multigroup and continuous nuclear data

The fast neutron fluence and the activation monitor activities are routinely calculated with TORT deterministic code and BUGLE-B7 nuclear data library with 47 broad energy groups. The objective of the paper is to analyse options to improve reactor dosimetry transport calculations. There are two paths to improve reactor dosimetry calculations. Increasing geometry, angular and energy mesh size is applicable for TORT code while using newer nuclear data libraries is relevant for both deterministic and Monte Carlo codes. Two new calculation options (improved TORT and Monte Carlo MCNP6) were compared with the standard TORT calculation for VVER-440 Dukovany Unit 3 Cycle 31. The fast neutron fluence with 0.5 MeV threshold as well as activity of Fe. Ni, Ti, Cu. Mn and Nb monitors were evaluated. Standard TORT calculations were improved from S16P3 to S30P3 with three times finer axial mesh size. 120° core symmetry r-ϑ mesh size with 0.5° step and fine multigroup libraries VUAMIN-B7 with 199 neutron energy groups and ENDF/B-VH.1 with 200 neutron energy groups. Both ENDFB and IRDFF activation cross sections were used. The drawback of expanded mesh size is raised calculation runtime since TORT deterministic code is not parallelized and one calculation can require multiple weeks of CPU time. An alternative option of using MCNP6 Monte Carlo code with continuous ENDF/B-VH.1 nuclear data with detailed 3-D geometry and pin-wise effective neutron source prepared by MOBY-DICK diffusion code reactor analysis wras explored. It was found that using finer mesh size affects reactor dosimetry’ tallies less than the choice of nuclear data library. BUGLE-B7 and VTTAMIN-B7 produce results typically within 1% difference. ENDF/B-VH.1 calculations with 200 neutron energy’ groups with TORT code are even in better agreement with MCNP6 calculations with continuous nuclear data libraries. The largest differences of around 2% were observed between VTTAMIN-B7 library based onENDFB-VH.O nuclear data and ENDF/B-VH.1 library. Nuclear data library’ has larger impact on the results with up to 7 % difference between all 0.5 MeV fast neutron fluence calculations. The largest intact of nuclear data was observed for Mn(n.2n) monitor.

Clinamen2: Functional-style evolutionary optimization in Python for atomistic structure searches

Clinamen2 is a versatile functional-style Python implementation of the covariance matrix adaptation evolution strategy (CMA-ES) utilizing Cholesky decomposition. On top of a problem-agnostic core algorithm, the software package offers a suite of utilities and library code enabling applications to important atomistic structure searches. Features include massively distributed computation and the BI-Population restart scheme. This article details the general code structure and introduces examples that illustrate some relevant applications for the materials science and chemistry worlds, including interfacing to density-functional-theory codes and machine-learned surrogate models. The functional design renders the code modular and adaptable, and makes the creation of interfaces to other atomistic software straightforward. Program summaryProgram Title: Clinamen2CPC Library link to program files:https://doi.org/10.17632/x7syr2txsd.1Developer's repository link:https://github.com/Madsen-s-research-group/clinamen2-public-releasesCode Ocean capsule:https://codeocean.com/capsule/4950229Licensing provisions: Apache-2.0Programming language: PythonSupplementary material:Nature of problem: Find optimal atomistic structures retaining full flexibility in the choice of the optimization target, the methodological approach and its implementation (e.g. CPU- vs. GPU-heavy calculations). Enable interfacing with relevant software, including but not limited to density-functional-theory (DFT) codes and machine-learning (ML) solutions.Solution method: The covariance matrix adaptation evolution strategy (CMA-ES) algorithm is implemented using Cholesky decompositions for efficiency. The core algorithm and application examples for specific problems are implemented in functional-style Python free of side effects, with data classes to keep track of the state of the evolution. Dask is used for job control to enable highly distributed workflows. Advanced strategies like BI-Population CMA-ES are easy to implement and illustrated in the examples.

Open access dataset, code library and benchmarking deep learning approaches for state-of-health estimation of lithium-ion batteries

Great progress has been made in deep learning (DL) based state-of-health (SOH) estimation of lithium-ion batteries, which helps to provide recommendations for predictive maintenance and replacement of lithium-ion batteries. However, despite the abundance of articles, few open-source codes are publicly available. While there are several public datasets, they tend to be more oriented toward simulating laboratory environments rather than real-world usage scenarios. Moreover, they solely provide raw data without any corresponding preprocessing codes, resulting in inconsistencies in preprocessing methods across different papers. These reasons lead to unfair comparisons and ineffective improvements. In response to these problems, this paper publishes a large-scale lithium-ion battery run-to-failure dataset, consisting of 55 batteries, and provides a unified data preprocessing method. Besides, we comprehensively evaluate 5 well-known DL-based models to provide benchmark research. To be specific, first, the existing DL-based SOH estimation methods are reviewed in detail. Second, we provide a comprehensive evaluation of DL-based models on 2 large-scale datasets, including 100 batteries, with 3 input types and 3 normalization methods. Third, we make the complete evaluation codes and dataset publicly available for better comparison and model improvement. Fourth, we discuss future DL-based SOH estimation, including unsupervised learning, transfer learning, interpretability, and physics-informed machine learning. We emphasize the importance of open-source code, provide baseline estimation errors (error upper bounds), and discuss existing issues in this field. The code library is available at: https://github.com/wang-fujin/SOHbenchmark.

Third-party software library migration at the method-level using multi-objective evolutionary search

Software developers commonly use third-party software libraries to reduce implementation efforts and mitigate errors in their source code while building high-quality and reliable software. To support software evolution, newer libraries are released periodically with added features, improvements in performance as well as critical updates such as bug fixes. Hence, older, existing (source) libraries need to be replaced with their newer, updated (target) counterparts, in a process known as library migration. Typically, library migration is a time-consuming, manual, and error-prone process that requires developers to analyze the source and target library code and its documentation. Specifically, developers examine Application Programming Interface (API) implementations and documentation to replace each source API with a target API without modifying the underlying software functionality. While recent works have used various techniques to recommend suitable target library replacements, these approaches do not generalize well, e.g., when a source library method needs to be replaced by one or more target library APIs or methods. To address this limitation, we propose the use of multi-objective evolutionary algorithms to identify suitable method replacements during library migration. In particular, we formulate library migration at the method-level as a multi-objective combinatorial optimization problem and examine the performance of 7 multi-objective evolutionary algorithms: UNSGAIII, RNSGAII, AGEMOEA, SMSEMOA, NSGAII, IBEA and MOEAD. We use method signature and documentation similarity, and co-occurrence probability to accurately recommend one or more target library methods. We evaluate our approach by conducting an empirical study on 9 popular Java library migrations mined from 57,447 open-source projects on GitHub. Our results demonstrate that UNSGAIII, RNSGAII, AGEMOEA, SMSEMOA, NSGAII, IBEA and MOEAD achieve 90%, 89%, 94%, 90%, 91%, 94%, and 71% precision on average, and 83%, 23%, 58%, 63%, 58%, 60% and 17% average recall respectively. In the interest of reproducibility, we make all code and results publicly available at: http://bit.ly/MOO-api-migration.

Static recording apparatus for soundscape analysis in Macau

The concept of Soundscape was initially proposed to study the relationship between humans and their sonic environment. It has gathered momentum from academia to environmentalists and policymakers throughout the years. The study and characterisation of Soundscapes can be complex as it tries to take a holistic and qualitative approach rather than simply quantifying sound pressure levels. This paper introduces a comprehensive Soundscape study process in an ongoing research project in Macao (China), a small territory (32.9 km2) and one of the most densely populated areas in the world. The paper seeks to show a first version of a technical solution to systematically capture the local soundscape, analyse it, classify it, and ultimately deliver a dataset library and the intangible qualities of the environmental sound. This implementation, including technical documentation, code, and sound library with strong labelling, is presented under an open-source license to encourage future collaborative research. Finally, the paper offers suggestions on further developing the apparatus to reach a systematic and near real-time soundscape analysis with the development of a machine learning system.

Ethical misconduct among librarians in selected nursing training colleges in Ghana

Every profession is guided by ethical conduct to help maintain the status quo of the profession. This study focused on assessing the ethical misconduct among librarians in selected nursing and midwifery training colleges in Ghana. The study adopted a qualitative research technique. Four head librarians were chosen using a purposive sampling approach each, from the three sectors demarcated by the researchers for the study. The findings from this study indicate that plagiarism is the most ethical misconduct librarians engage in, followed by violation of intellectual property rights and lack of access to information. The study also reveals that quick turnaround for searches, inadequate funds, ignorance of the code of ethics, and lack of education are the main causes of information ethical misconduct in librarianship. The study recommends that enough funding must be given to Nursing and Midwifery Training College (NMTC) libraries by management in order to equip them with the acquisition of legitimate materials to help curtail the violation of intellectual property rights and all other forms of ethical misconduct and dilemmas as a whole. Furthermore, the researchers propose that the Ghana Library Association which is the body responsible for librarians' interests should revise the 2014 Library Code of Ethics and urgently hold a seminar/workshop to refresh members' knowledge of the Code of Ethics.

Modeling of non-homogeneous premixed hydrogen-air flame acceleration and deflagration to detonation transition in an obstructed channel

This paper uses Large Eddy Simulation (LES) technology to study the dynamic behavior of flame acceleration (FA) and deflagration-to-detonation transition (DDT) in a duct with different obstacle layouts in non-homogeneous concentration fields. A turbulent premixed combustion model with three additional source terms was established using the OpenFoam code library. It was found that the predicted results of the coupled model were in good agreement with the measured values of the experiment. Numerical results show that turbulent combustion and self-ignition effects are the main factors affecting flame acceleration. Still, self-ignition effects are a necessary and sufficient condition for inducing DDT phenomena. Detonation flames have around-flow and diffraction effects and do not evolve into jet and vortex flames, which differ from deflagration flames. Two initiation mechanisms were found under different obstacle layouts: hotspots were generated in the area swept by the Mach stem at the flame front, triggering detonation near the turbulent flame through the reactive gradient mechanism; focusing of sufficiently strong reflected waves deposited enough energy in a particular area near the flame brush and directly triggered detonation. In addition, the central obstacle layout is most conducive to FA and DDT, while the symmetrical layout is the least favorable.

Analyzing beam-gas interactions in an cyclotron beam

For the Isotope Decay At Rest (IsoDAR) experiment in neutrino physics (searching for sterile neutrinos), we have developed a novel compact isochronous cyclotron with direct injection through an axially embedded RFQ. For IsoDAR to be decisive within five years of running, 10 mA of protons, cw at 80% duty factor are needed on a neutrino production target. To alleviate space charge in the cyclotron driver, we accelerate 5 mA of , to be broken up into 10 mA of protons after extraction from the cyclotron. An open question that we are answering with this paper is whether the beam losses from gas-stripping (the removal of electrons from through the interaction of the beam ions with the residual gas in the accelerator) are going to be a significant challenge. Using a newly added feature to the well-established Object-Oriented Parallel Accelerator Library code, we calculate gas-stripping losses in the IsoDAR cyclotron using realistic beam distributions, magnetic fields, gas composition, and pressure. We show that to maintain losses due to dissociation below 1% over the entire acceleration region, a vacuum of at least 6 × 10−7 mbar is required.

Development of an Algorithm to Evaluate the Quality of Geolocated Addresses in Urban Areas

The spatial and semantic data of geographic addresses are extremely important for citizens, governments, and companies. The addresses can georeference environmental, economic, security, health, and demographic parameters in urban areas. Additionally, address components can be used by users to locate any point of interest (POI) with location-based systems (LBSs). For this reason, errors in address data can affect the geographic location of events, map representations, and spatial analyses. Thus, this paper presents the development of an algorithm for evaluating the quality of semantic and geographic information in any geospatial address dataset. The reference datasets are accessible using open data platforms or spatial data infrastructure (SDI) and volunteered geographic information (VGI), and both have been compared with commercial datasets using geocoding web services. Address quality analysis was developed using several open-source data science code libraries combined with spatial databases and geographic information systems. In addition, the quality of geographic addresses was evaluated by carrying out normalized tests in accordance with International Geospatial Standards (ISO 19157). Finally, this methodology assesses the quality of authorized and VGI address datasets that can be used for geocoding any relevant information in specific urban areas.