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A Visualization Approach for Simulating and Analyzing Infection Spread Dynamics Using Temporal Networks 利用时间网络模拟和分析感染传播动态的可视化方法
J. Inf. Data Manag. Pub Date : 2022-09-12 DOI: 10.5753/jidm.2022.2456
Jean R. Ponciano, Gabriel P. Vezono, Claudio D. G. Linhares
{"title":"A Visualization Approach for Simulating and Analyzing Infection Spread Dynamics Using Temporal Networks","authors":"Jean R. Ponciano, Gabriel P. Vezono, Claudio D. G. Linhares","doi":"10.5753/jidm.2022.2456","DOIUrl":"https://doi.org/10.5753/jidm.2022.2456","url":null,"abstract":"Temporal networks have been widely used to model instances of a domain of interest and their time-evolving interaction, including modeling individuals and face-to-face contacts throughout time. In the context of infection spread, such individuals can, e.g., remain susceptible, recovered, or be infected at a particular time. Understanding the infection spread behavior (its speed and magnitude, for instance) is crucial for quick and reliable decision making. Network visualization strategies can help in this task as they allow easy identification of who infected whom and when, epidemics outbreak, and other relevant aspects. This paper presents a visualization approach for the simulation and analysis of infection spread dynamics that considers different infection probabilities and different levels of social distancing (inter-group interaction). We performed quantitative and visual experiments using three real-world social networks with distinct characteristics and from two different environments. Our findings reveal the overall influence of different levels of inter-group interaction and infection probabilities in the infection spread dynamics and also demonstrate the usefulness of our approach for enhanced local (individual- or group-level) investigations.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126964675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Comprehensive Dataset of Brazilian Fact-Checking Stories 巴西事实核查故事的综合数据集
J. Inf. Data Manag. Pub Date : 2022-08-15 DOI: 10.5753/jidm.2022.2354
Igor Marques, Isadora Salles, João M. M. Couto, Breno C. Pimenta, Samuel Assis, Julio C. S. Reis, Ana P. C. Silva, J. Almeida, Fabrício Benevenuto
{"title":"A Comprehensive Dataset of Brazilian Fact-Checking Stories","authors":"Igor Marques, Isadora Salles, João M. M. Couto, Breno C. Pimenta, Samuel Assis, Julio C. S. Reis, Ana P. C. Silva, J. Almeida, Fabrício Benevenuto","doi":"10.5753/jidm.2022.2354","DOIUrl":"https://doi.org/10.5753/jidm.2022.2354","url":null,"abstract":"In recent years, digital platforms have become a powerful means for large scale information diffusion world-wide, particularly in Brazil. Understanding key aspects driving the misinformation diffusion process is of paramountimportance to the design and implementation of new tools to automatically detect misinformation content. In this scenario, fact-checking performed by high credibility agencies provide rich labeled data, which is fundamental to build tools capable of detecting and mitigating the effects of misinformation. This paper opens a novel dataset, referred to as FactCenter, to the research community, containing fact-check instances collected from 6 different Brazilian fact-checking agencies. This dataset has 11 647 fact-check instances, covering several topics and domains. We present an initial analysis of the data collected, enriched by data from Facebook, which demonstrates the potential of our repository for future studies.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114205244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
BovDB: a data set of stock prices of all companies in B3 from 1995 to 2020 BovDB: B3中所有公司1995年至2020年的股价数据集
J. Inf. Data Manag. Pub Date : 2022-08-15 DOI: 10.5753/jidm.2022.2345
Fabian Corrêa Cardoso, J. Malska, P. Ramiro, Giancarlo Lucca, E. Borges, V. Mattos, R. Berri
{"title":"BovDB: a data set of stock prices of all companies in B3 from 1995 to 2020","authors":"Fabian Corrêa Cardoso, J. Malska, P. Ramiro, Giancarlo Lucca, E. Borges, V. Mattos, R. Berri","doi":"10.5753/jidm.2022.2345","DOIUrl":"https://doi.org/10.5753/jidm.2022.2345","url":null,"abstract":"Stock markets are responsible for the movement of vast amounts of financial resources worldwide. This market generates a high volume of transaction data, which after being analyzed are very useful for many applications. In this article, we present BovDB, a data set that was built considering a source of the Brazilian Stock Exchange (B3) with information related to the years between 1995 and 2020. We have approached the events’ impact on the stocks byapplying a cumulative factor to correct prices. The results were compared with public data from InfoMoney and BR Investing, showing that our methods, are valid and follow the market standards, based on the proposed factor. BovDBdata set can be used as a benchmark for different applications and it is available in open access for any researcher on GitHub.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127698077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
CandiDATA: an enhanced dataset for data analysis of elections in Brazil from 1945 to 2020 CandiDATA:一个增强的数据集，用于分析1945年至2020年巴西选举的数据
J. Inf. Data Manag. Pub Date : 2022-08-15 DOI: 10.5753/jidm.2022.2361
Felipe F. Vasconcelos, João V. S. Tavares, Matheus G. S. Oliveira, Fábio Coutinho, João Paulo Clarindo
{"title":"CandiDATA: an enhanced dataset for data analysis of elections in Brazil from 1945 to 2020","authors":"Felipe F. Vasconcelos, João V. S. Tavares, Matheus G. S. Oliveira, Fábio Coutinho, João Paulo Clarindo","doi":"10.5753/jidm.2022.2361","DOIUrl":"https://doi.org/10.5753/jidm.2022.2361","url":null,"abstract":"The Brazilian Superior Electoral Court (TSE) keeps data on elections that have taken place in Brazil since 1933. These data constitute an important collection serving as a reference for works in several research areas. However, this collection is not fully exploited due to some problems, such as missing and non-standard data, making analysis and integration with external databases difficult. Previous works built limited datasets and tools because of these problems as they only include data since the 1998 election, disregarding the election years from 1945 and 1996. This work discusses the steps to create CandiDATA – a standardized and enhanced dataset from TSE data, including a toolkit of webscrapping and data visualization. CandiDATA is available in open format and covers the election period between 1945 and 2020.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121081550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Cross-collection Dataset of Public Domain Portuguese-language Works 公共领域葡萄牙语作品交叉收集数据集
J. Inf. Data Manag. Pub Date : 2022-08-15 DOI: 10.5753/jidm.2022.2349
Mariana O. Silva, Clarisse Scofield, Luiza de Melo-Gomes, Mirella M. Moro
{"title":"Cross-collection Dataset of Public Domain Portuguese-language Works","authors":"Mariana O. Silva, Clarisse Scofield, Luiza de Melo-Gomes, Mirella M. Moro","doi":"10.5753/jidm.2022.2349","DOIUrl":"https://doi.org/10.5753/jidm.2022.2349","url":null,"abstract":"Many datasets are published in English to get more engagement, popularity and reach within a research community. Indeed, most sciences are language-agnostic and thrive on publicly available data. However, such a claim is not always valid for Arts, where Literature and Music are two examples of fields that heavily rely on the language of the work. Especially in Literature, combining human expertise with book consumers’ data may generate what is needed to sustain constant changes experienced in the book publishing market. Therefore, we introduce PPORTAL, the first public domain Portuguese-language literature dataset that is composed of a wide variety of book-related metadata. Afterintroducing its building process and content, we present an exploratory data analysis with a quantitative description of its main features. We also show its usability as a resource on different research domains through examples of real-world applications, as well as pointing out other potential applications.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132733741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PolRoute-DS: a Crime Dataset for Optimization-based Police Patrol Routing PolRoute-DS:基于优化的警察巡逻路线犯罪数据集
J. Inf. Data Manag. Pub Date : 2022-08-15 DOI: 10.5753/jidm.2022.2355
Bruno Cunha Sá, Gustavo Muller, Maicon Banni, Wagner Santos, Marcos Lage, Isabel Rosseti, Yuri Frota, Daniel de Oliveira
{"title":"PolRoute-DS: a Crime Dataset for Optimization-based Police Patrol Routing","authors":"Bruno Cunha Sá, Gustavo Muller, Maicon Banni, Wagner Santos, Marcos Lage, Isabel Rosseti, Yuri Frota, Daniel de Oliveira","doi":"10.5753/jidm.2022.2355","DOIUrl":"https://doi.org/10.5753/jidm.2022.2355","url":null,"abstract":"It is a well-known fact that criminality is an open, yet important, issue in most urban centers worldwide. Especially in Brazil, creating solutions to reduce crime rates is a top priority. To reduce crime rates, many cities are adopting predictive policing techniques. Predictive policing techniques are highly based on extracting valuable knowledge from a massive dataset that contains information about times, locations, and types of past crimes. The extracted knowledge is then used to provide insights to police departments to define where the police must maintain its presence. These datasets may also be used for a critical predictive policing task: defining where police patrols should patrol. Such patrols are commonly defined to cover a series of crime hot spots (areas that present high criminality levels) and have some restrictions to be considered (number of available police officers, cars, etc). Thus, defining the route for each police vehicle is a complex optimization problem, since in most cases, there are many hot spots and the existing resources are scarce, i.e., the amount of vehicles and police available is much smaller than necessary. Unfortunately, high-quality crime rates data are not easy to obtain. Aiming to tackle this problem, this article proposes the PolRoute-DS dataset, a dataset designed to foster the development and evaluation of police routing approaches in large urban centers. The PolRoute-DS combines the spatial structure of the city of interest (in the context of this article, the city of São Paulo) represented as a connected and directed graph of street segments with criminal data obtained from public sources. PolRoute-DS is available for public use under the Creative Commons By Attribution 4.0 International license (CSV and PostgreSQL versions) and can be downloaded at https://osf.io/mxrgu/.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128762548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Curating, Enriching and FAIRifying Datasets from the Brazilian COVID-19 Vaccination 管理、丰富和公平化巴西COVID-19疫苗接种数据集
J. Inf. Data Manag. Pub Date : 2022-08-15 DOI: 10.5753/jidm.2022.2356
Marcus Vinicius Ferreira Gonçalves, Jamile Santos, Caio Zava Ferreira, Jorge Juan Zavaleta Gavidia, Sérgio Manuel Serra da Cruz, Jonice Oliveira
{"title":"Curating, Enriching and FAIRifying Datasets from the Brazilian COVID-19 Vaccination","authors":"Marcus Vinicius Ferreira Gonçalves, Jamile Santos, Caio Zava Ferreira, Jorge Juan Zavaleta Gavidia, Sérgio Manuel Serra da Cruz, Jonice Oliveira","doi":"10.5753/jidm.2022.2356","DOIUrl":"https://doi.org/10.5753/jidm.2022.2356","url":null,"abstract":"As the world struggles to face the challenges of vaccination against COVID-19, more attention needs to be paid to the issues related to the lack of transparency and accessibility of curated vaccination datasets. Among the strategies to combat COVID-19, vaccination and data-centered epidemiological investigations are the best ones. This paper presents the process of building cured and annotated datasets with provenance metadata. The primary dataset is based on the registration data of the Vaccination Campaign against COVID-19 in Brazil. The dataset contains thousands of records processed up to March 2021. The data were analyzed, treated, cross-checked, and linked with other sources to correct and complement them, resulting in cured datasets and aligned to the FAIR Data principles.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129311655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Covid Data Analytics Repository: An interdisciplinary look into the COVID-19 pandemic in Brazil Covid数据分析库:对巴西Covid -19大流行的跨学科研究
J. Inf. Data Manag. Pub Date : 2022-08-15 DOI: 10.5753/jidm.2022.2266
Ramon A. S. Franco, Pedro Loures Alzamora, Janaína Guiginski, Evandro Cunha, Tereza Bernardes, J. F. Galindo, Luana Passos, R. Schneider, Bruno Chagas, Kícila Ferreguetti, L. Cardoso, Pedro Moreira, Wallace Pereira, Ana Paula Couto da Silva, Wagner Meira
{"title":"Covid Data Analytics Repository: An interdisciplinary look into the COVID-19 pandemic in Brazil","authors":"Ramon A. S. Franco, Pedro Loures Alzamora, Janaína Guiginski, Evandro Cunha, Tereza Bernardes, J. F. Galindo, Luana Passos, R. Schneider, Bruno Chagas, Kícila Ferreguetti, L. Cardoso, Pedro Moreira, Wallace Pereira, Ana Paula Couto da Silva, Wagner Meira","doi":"10.5753/jidm.2022.2266","DOIUrl":"https://doi.org/10.5753/jidm.2022.2266","url":null,"abstract":"This article describes the construction and deployment of the Covid Data Analytics Repository, a source for interdisciplinary studies about the impact of the COVID-19 pandemic in Brazil. We collected different types of data from official (IBGE, DATASUS) and non-official (Brasil.IO) sources, online social networks (Instagram, Twitter), and from a search engine analysis tool (Google Trends). We used these data to perform investigations aimed to understand the impacts of COVID-19 in the country, from economics to social behavior. At the moment of publication of this article, our repository contains 1,508 documents, classified into two main types: (i) databases and tables downloaded from the aforementioned sources; and (ii) papers, reports, maps and graphs resulting from the analyses that we performed. As a means to allow reproducibility and foster follow-up studies, we released our repository for public use.","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117342456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Frontmatter 头版头条
J. Inf. Data Manag. Pub Date : 2021-12-01 DOI: 10.1515/jaa-2021-frontmatter2
{"title":"Frontmatter","authors":"","doi":"10.1515/jaa-2021-frontmatter2","DOIUrl":"https://doi.org/10.1515/jaa-2021-frontmatter2","url":null,"abstract":"","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134440578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Frontmatter
J. Inf. Data Manag. Pub Date : 2021-11-27 DOI: 10.1515/jah-2021-frontmatter2
{"title":"Frontmatter","authors":"","doi":"10.1515/jah-2021-frontmatter2","DOIUrl":"https://doi.org/10.1515/jah-2021-frontmatter2","url":null,"abstract":"","PeriodicalId":301338,"journal":{"name":"J. Inf. Data Manag.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121659808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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