Update: We updated the data set in March 2022 by adding newly published papers and by providing more insights on how we analyzed them. Details can be found in the file " SEnti-SMS.xlsx".

Update: The updated version (-v2) contains the results of one more snowballing iteration and extracted information on the accuracy of the used methods.

In 2020, we conducted a systematic literature review to explore the development and application of sentiment analysis tools in software engineering.

Information on the execution of the SLR, its scope, the search string, etc. are presented in the paper linked below.

👨‍💻 Author: Azhar Saleem

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Dataset Overview

Welcome to the Google Places Comprehensive Business Dataset! This dataset has been meticulously scraped from Google Maps and presents extensive information about businesses across several countries. Each entry in the dataset provides detailed insights into business operations, location specifics, customer interactions, and much more, making it an invaluable resource for data analysts and scientists looking to explore business trends, geographic data analysis, or consumer behaviour patterns.

Key Features

• Business Details: Includes unique identifiers, names, and contact information.
• Geolocation Data: Precise latitude and longitude for pinpointing business locations on a map.
• Operational Timings: Detailed opening and closing hours for each day of the week, allowing analysis of business activity patterns.
• Customer Engagement: Data on review counts and ratings, offering insights into customer satisfaction and business popularity.
• Additional Attributes: Links to business websites, time zone information, and country-specific details enrich the dataset for comprehensive analysis.

Potential Use Cases

This dataset is ideal for a variety of analytical projects, including: - Market Analysis: Understand business distribution and popularity across different regions. - Customer Sentiment Analysis: Explore relationships between customer ratings and business characteristics. - Temporal Trend Analysis: Analyze patterns of business activity throughout the week. - Geospatial Analysis: Integrate with mapping software to visualise business distribution or cluster businesses based on location.

Dataset Structure

The dataset contains 46 columns, providing a thorough profile for each listed business. Key columns include:

• business_id: A unique Google Places identifier for each business, ensuring distinct entries.
• phone_number: The contact number associated with the business. It provides a direct means of communication.
• name: The official name of the business as listed on Google Maps.
• full_address: The complete postal address of the business, including locality and geographic details.
• latitude: The geographic latitude coordinate of the business location, useful for mapping and spatial analysis.
• longitude: The geographic longitude coordinate of the business location.
• review_count: The total number of reviews the business has received on Google Maps.
• rating: The average user rating out of 5 for the business, reflecting customer satisfaction.
• timezone: The world timezone the business is located in, important for temporal analysis.
• website: The official website URL of the business, providing further information and contact options.
• category: The category or type of service the business provides, such as restaurant, museum, etc.
• claim_status: Indicates whether the business listing has been claimed by the owner on Google Maps.
• plus_code: A sho...

This file presents the catalog of metrics and the topic independent classification done.

Mapping Software Market size was valued at USD 8.2 Billion in 2024 and is projected to reach USD 17.5 Billion by 2032, growing at a CAGR of 9.7% during the forecast period 2026-2032.Real-time location data is used for navigation, route planning, and traffic monitoring, resulting in increased efficiency in transportation and delivery operations.

Curriculum Mapping Software Market Outlook

The global curriculum mapping software market size was valued at USD 1.2 billion in 2023 and is expected to reach an estimated USD 3.8 billion by 2032, growing at a CAGR of 13.2% during the forecast period from 2024 to 2032. This significant growth can be attributed to the increasing emphasis on personalized learning experiences, the necessity for compliance with educational standards, and the growing adoption of digital tools in the education sector.

One of the primary growth factors for the curriculum mapping software market is the rising demand for personalized and adaptive learning solutions. Educational institutions are increasingly leveraging technology to design curricula that cater to individual student needs. This shift not only enhances the learning experience but also improves student performance and engagement. Additionally, the ability of curriculum mapping software to help educators identify gaps in the curriculum and align teaching methods with learning objectives contributes significantly to its adoption.

Another driving force behind the market's growth is the increased focus on compliance with educational standards and accreditation requirements. Curriculum mapping software allows institutions to systematically design, implement, and review curricula to ensure they meet the necessary standards and regulations. This capability is particularly crucial for higher education institutions seeking accreditation or re-accreditation, as it provides a clear, organized, and accessible record of curriculum alignment and effectiveness.

The growing integration of data analytics and artificial intelligence in curriculum mapping software also plays a crucial role in market expansion. These technologies enable the software to offer advanced analytics, predictive modeling, and insights, which help educators make informed decisions about curriculum design and instruction. The ability to analyze student performance data and predict learning outcomes can facilitate proactive interventions, thus improving the overall educational experience.

Regionally, North America is expected to dominate the market due to the early adoption of advanced educational technologies, the presence of prominent market players, and substantial government funding for educational innovations. However, the Asia Pacific region is anticipated to exhibit the highest growth rate during the forecast period. Countries such as China, India, and Japan are investing heavily in educational technology to enhance their education systems, driven by the increasing demand for skilled professionals and the need for modernized educational infrastructure.

In addition to curriculum mapping software, educational institutions are increasingly turning to Gradebook Software to streamline their assessment and grading processes. Gradebook Software provides educators with a comprehensive platform to manage student grades, track academic progress, and generate detailed reports. This software not only simplifies the grading process but also enhances transparency and communication between teachers, students, and parents. By integrating Gradebook Software with curriculum mapping tools, institutions can create a cohesive educational ecosystem that supports personalized learning and data-driven decision-making. The growing demand for efficient and user-friendly grading solutions is driving the adoption of Gradebook Software across various educational settings.

Component Analysis

The curriculum mapping software market can be segmented based on components into software and services. The software segment accounts for the largest share of the market, driven by the increasing adoption of digital platforms for curriculum design and management. Educational institutions are recognizing the benefits of using specialized software to streamline and enhance the curriculum development process. This software facilitates the creation, organization, and assessment of curricula, providing educators with tools to align instructional practices with learning objectives effectively.

Within the software segment, the market is further divided into cloud-based and on-premises solutions. Cloud-based curriculum mapping software is gaining significant traction due to its scalability, flexibility, and cost-effectiveness. These solutions allow institutions to access the software from anywhere, at any time, and often come with automatic updates

Protocol, extraction form, and data set resulting from conducting an SMS on Integrated Operating Rooms (IORs)

Domain-specific languages (DSL) are programming or modeling languages devoted to a given application domain. There are many tools used to support the implementation of a DSL, making hard the decision-making process for one or another. In this sense, identifying and mapping their features is relevant for decision-making by academic and industrial initiative on DSL development. Objective: The goal of this work is to identify and map the tools, Language Workbenches (LW), or frameworks that were proposed to develop DSLs discussed and referenced in publications between 2012 and 2019. Method: A Systematic Mapping Study (SMS) of the literature scoping tools for DSL development. Results: We identified 59 tools, including 9 under a commercial license and 41 with non-commercial licenses, and analyzed their features from 230 papers. Conclusion: There is a substantial amount of tools that cover a large number of features. Furthermore, we observed that usually, the developer adopts one type of notation to implement the DSL: textual or graphical. We also discussed research gaps, such as a lack of tools that allow meta-meta model transformations and that support modeling tools interoperability.

Contains spreadsheets used to report findings in the "Application of Collaborative Learning Paradigms within Software Engineering Education: A Systematic Mapping Study" paper.

This dataset includes the set of papers retrieved to perform a systematic mapping review (SMR) on multi-paradigm modelling (MPM) for cyber-physical systems (CPS). Moreover, it includes several tables that map the studies under several perspectives, notably used modelling formalisms and processes, part of the CPS addressed by the research, domain of expertise of paper authors, and relevance of the paper at review date. The set of papers is selected over a period ranging from 2006 to 2017, according to publication dates. The selection of the papers and their mapping has been performed by means of a rigorous process based on precise aspects to be evaluated and peer reviewing. Further, the process has been supported by a web-based survey management application. Both the selection of existing publications and their mappings by means of the included perspectives provide interested readers/researches with interesting data possible re-usable for multiple purposes: analysing the progress of research on modelling of CPS, studying further the papers pertaining to a specific (set of) characteristic(s), performing a follow-up study related to other development technologies, just to mention a few.

The post-digital era is characterized by the vast presence of platforms imposing their digital affordances and algorithmic control on our behavior. This environment is challenging education and training, with implications for digital and transmedial literacy. Investigating instructional methodologies is crucial to foster critical comprehension of such novel informational environments. The argument maps (AM), which were first created and evaluated in static information contexts (analogical/old web), could be useful in the emergence of dynamic (post-digital) textual forms.

The current paper describes a comprehensive literature review based on the assumptions above. We looked into state of the art in research on using AM to handle dynamic information. We found 150 papers using a PRISMA procedure and then examined 25 of them. Our review produced pertinent data about the current state of AM, including the sorts of texts on which they are used and the tools (especially digital and AI-based) that have been employed. Our research lays the groundwork for teaching the literacies needed in new informational settings, such as multimodal, dynamic, algorithmic, and data-driven contexts, with a specific focus on AM as an effective mediational tool.

This Zenodo record presents the full dataset composed of the following sheets:

Codebook

Italian Journals

List of articles extracted from SCOPUS

List of articles extracted from ERIC

List of articles extracted from WOS

List of articles extracted from DOAJ

PRISMA workflow

Analysis - First Level (classification of 25 articles selected)

Analysis - Second Level (List of 19 articles selected)

Final Dataset

Interrater Agreement.

As for the Keywords' Map, a primo file .txt displays the text over which basis was performed the keyword maps analysis. The second .txt file shows notes relating to the analysis procedures using the software VOS-Viewer http://www.vosviewer.com/

Any comments or improvements are welcome!

The Indoor Mapping Software market is experiencing significant growth as organizations increasingly recognize the importance of spatial data in enhancing operational efficiency and user experiences. This software provides a sophisticated solution for visualizing and navigating indoor spaces, whether in large facilit

This repository contains al the artifacts of the research: Bots in Software Development: A Systematic Literature Review

Context: Software defect prediction is a trending research topic, and a wide variety of the published papers focus on coding phase or after. A limited number of papers, however, includes the prior (early) phases of the software development lifecycle (SDLC). Objective: The goal of this study is to obtain a general view of the characteristics and usefulness of Early Software Defect Prediction (ESDP) models reported in scientific literature. Method: A systematic mapping and systematic literature review study has been conducted. We searched for the studies reported between 2000 and 2016. We reviewed 52 studies and analyzed the trend and demographics, maturity of state-of-research, in-depth characteristics, success and benefits of ESDP models. Results: We found that categorical models that rely on requirement and design phase metrics, and few continuous models including metrics from requirements phase are very successful. We also found that most studies reported qualitative benefits of using ESDP models. Conclusion: We have highlighted the most preferred prediction methods, metrics, datasets and performance evaluation methods, as well as the addressed SDLC phases. We expect the results will be useful for software teams by guiding them to use early predictors effectively in practice, and for researchers in directing their future efforts.

Mind Mapping Tools Market size was valued at USD 1.4 Billion in 2023 and is expected to reach USD 2.8 Billion by 2031 with a CAGR of 9.6% from 2024-2031.

Global Mind Mapping Tools Market Drivers

The market drivers for the Mind Mapping Tools Market can be influenced by various factors. These may include:

Increased Adoption of Digital Collaboration Tools: With the rise of remote work and online collaboration, organizations are increasingly seeking digital tools that enhance teamwork and idea sharing. Mind mapping tools facilitate brainstorming and visual organization of thoughts, making them appealing for collaborative projects. Growing Emphasis on Visual Learning and Thinking: There is a growing recognition of the value of visual tools in enhancing learning and comprehension. Mind mapping caters to visual learners and helps users organize information in a more intuitive manner, thereby driving adoption in educational settings.

Database of mapping studies version 6 110717. Data extraction table. Spreadsheet copy of the data extraction table, giving details of the studies meeting inclusion criteria. (XLSX 285 kb)

Application Dependency Mapping Tools Market was valued at USD 0.9 Billion in 2024 and is projected to reach USD 2.1 Billion by 2032, growing at a CAGR of 11.2% during the forecast period 2026–2032.Rising Complexity of IT Environments: Increasing complexity in enterprise IT systems, with cloud and hybrid architectures, drives demand for dependency mapping tools to optimize performance. The system visibility And IT efficiency fuels sales.

Additional file 1. Database of systematic reviews and maps and descriptive information about their database formats. https://doi.org/10.6084/m9.figshare.13019186 .

This meta-analysis compared beat-based musical rhythms to non-beat-based musical rhythms.

Collection description

Maps corresponding to the paper "Identifying a brain network for musical rhythm: A functional neuroimaging meta-analysis and systematic review" . Meta-analyses were conducted in the Seed-based d mapping software (SDM-PSI, version 6.12) All maps in this collection contain corrected 1-p values that were set using threshold-free cluster enhancement (TFCE). Correction for multiple comparisons was achieved through 1000 permutations of subject images to control the familywise error rate (FWER). Maps are unthresholded.

Kasdan, A. V., Burgess, A. N., Pizzagalli, F., Scartozzi, A., Chern, A., Kotz, S. A., Wilson, S.M. & Gordon, R. L. (2022). Identifying a brain network for musical rhythm: A functional neuroimaging meta-analysis and systematic review. Neuroscience & Biobehavioral Reviews, 104588. DOI: https://doi.org/10.1016/j.neubiorev.2022.104588

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

meta-analysis

Cognitive paradigm (task)

music comprehension/production

Map type

IP

Replication package of the study "Grey Literature in Software Engineering: A Critical Review" published in Information and Software Technology (IST).

The Mapping Software market has evolved significantly over the past decade, emerging as a vital tool across various industries such as transportation, real estate, urban planning, and logistics. As organizations strive for enhanced efficiency and competitive advantage, mapping software provides comprehensive solutio