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Day 1 17/04/2020
Room #1

Opening 08:00 - 08:20

Welcome speech by General Chair 08:20 - 08:30

Welcome speech by Conference Manager 08:30 - 08:40

Keynote speech-Prof. Miriam Capretz 08:40 - 09:20

Title: Big Data Opportunities, Challenges and Applications

Keynote speech-Prof. Mario Dantas 09:20 - 10:10

Title: Data-Intensive Scalable Computing

Break 10:10 - 10:30

Session 1 10:30 - 11:30

Session Chair: Moisés Lima Dutra (20 minutes for presentation and 5-10 minutes for questions)
11:30 - 12:00
Data Management Plan in Research: Characteristics and Development

Data science is an interdisciplinary field that extracts value from data. One of the relevant areas is its application in research in order to define requirements of the data life cycle. Thus, data should be managed before, during, and after a research project completion. A robust data management plan (DMP) is a relevant and useful instrument to establish data-related requirements. In this context, this paper aims at highlighting some characteristics associated to research data management. To conduct this study peer-reviewed literature and secondary data are methodologically employed to fulfil the paper objective. The results discuss the development of DMP, provide some examples of documents and a check list related to data management, and present some recommendations for developing a suitable data management plan from the literature. The data management plan is one of the important instruments that should be considered with care when designing and applying it. Future work may consider providing a structure and guidance for research students in the field of industrial engineering as a valuable avenue to explore.
Authors: Paulo A. Cauchick Miguel (Universidade Federal de Santa Catarina - UFSC), Suzana Moro (Universidade Federal de Santa Catarina - UFSC), Roberto Rivera (Universidade de Aveiro), Marlene Amorim (Universidade de Aveiro),
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12:00 - 12:30
A Blockchain Approach to Social Responsibility

As blockchain technology matures, more sophisticated solutions arise regarding complex problems. Blockchain continues to spread towards various niches such as government, IoT, energy, and environmental industries. One often overlooked opportunity for blockchain is the social responsibility sector. Presented in this paper is a permissioned blockchain model that enables enterprises to come together and cooperate to optimize their environmental and societal impacts. This is made possible through a private or permissioned blockchain. Private blockchains are blockchain networks where all the participants are known and trust relationships among them can be fostered more smoothly. An example of what a private blockchain would look like is described in thispaper as well as its implementation, achieved using Hyperledger Fabric, which is a business-oriented blockchain framework. This study touches on the benfits available for companies that are willing to engage in socially responsible causes through blockchain. It states in what ways a permissioned blockchain can bring together businesses on common ground to increase their reach and provide better customer service. Finally, a use case is provided to bring to life a real-world situation where blockchain use improves service quality for all the parties involved, both the companies and their customers.
Authors: Augusto Bedin (Western University), Wander Queiroz (Western University), Miriam Capretz (Western University), Syed Mir (London Hydro),
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12:30 - 13:00
A Method for Clustering and Predicting Stocks Prices by using Recurrent Neural Networks

Predicting the stock market is a widely studied field, either due to the curiosity in finding an explanation for the behavior of financial assets or for financial purposes. Among these studies the best techniques use neural net-works as a prediction tool. More specifically, the best networks for this purpose are called recurrent neural networks (RNN) and provide an extra option when dealing with a sequence of values. However, a great part of the studies is intended to predict the result of few stocks, therefore, this work aims to predict the behavior of a large number of stocks. For this, similar stocks were grouped based on their correlation and later the algorithm K-means was applied so that similar groups were clustered. After this process, the Long Short-Term Memory (LSTM) - a type of RNN - was used in order to predict the price of a certain group of assets. Results showed that cluster-ing stocks did not influence the effectiveness of the network and that investors and portfolio managers can use it to simply their daily tasks.
Authors: Felipe Affonso (Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG)), Thiago Dias (Centro Federal de Educação Tecnológica de Minas Gerais (CEFET)), Adilson Pinto (UFSC),
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Session 2 11:30 - 12:30

Session Chair: Carlos Luis González Valiente (20 minutes for presentation and 5-10 minutes for questions)
14:30 - 15:00
Characterization of Women’s Scientific Participation in Brazil

Several researchers have concentrated efforts to study the participation of women in scientific and technological careers, seeking to profile their trajectory and academic performance in science. In this context, this study aimed to analyze the participation of the group of doctor’s degree who have curricula registered in the Lattes Platform and whose registered gender is female. After data collection, the stage of selection of curricula by gender criteria was performed, and data processing obtained a set of 149,850 registered curricula with female gender and maximum completed doctor’s degree distributed in its various areas of scientific knowledge. The doctor’s degree data were grouped regarding academic background, publications, productions, orientations, major areas of expertise and it was possible to analyze the evolution of scientific and technological production of the set in a temporal way. Studying the various aspects of gender difference in general and particularly in science and technology, as well as being relevant, can be a source of inspiration for government policies and programs that seek to promote change, encourage and value women’s participation in science.
Authors: Monique Santiago (Centro Federal de Educação Tecnológica de Minas Gerais (CEFET)), Thiago Dias (Centro Federal de Educação Tecnológica de Minas Gerais (CEFET)), Felipe Affonso (Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG)),
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15:00 - 15:30
Relations between the concepts of disinformation and the Fogg Behavior Model

This article aims to relate the concepts of false news and disinfor-mation with the Fogg Behavior Model (FBM) in order to observe their existing connections. For this, two steps were carried out: a) Identify five concepts of fake news or disinformation of organs or institutions that work on information, education, science and/or society issues; and b) Relate the concepts of fake news or disinformation found with Fogg Behavior Model. The research has a qualitative approach, having characteristics of exploratory and documentary re-search. It is concluded that there were links between definitions of disinfor-mation and fake news by UNESCO (United Nations Educational, Scientific and Cultural Organization), European Commission, Dictionary Oxford, World Eco-nomic Forum and Reuters with FBM with diverse levels of similarity. Through this analysis it is possible to learn more about how false information is formu-lated and how it can influence human behavior.
Authors: Enrique Muriel-Torrado (UFSC), Danielle Borges Pereira (UFSC),
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15:30 - 16:00
A strategy for co-authorship recommendation: Analysis Using Scientific Data Repositories

A strategy for co-authorship recommendation: Analysis Using Scientific Data Repositories In a co-authorship network papers written together represent the edges, and the authors represent the nodes. By using the concepts of social network analysis, it is possible to better understand the relationship between these nodes. At this point, the following question arises: "How does the evolution of the network occur over time?". In order to answer this question, it is necessary to understand how two nodes interact with one another, that is, what factors are essential for a new connection to be created. The purpose of this paper is to predict connections in co-authorship networks formed by doctors with resumes registered in the Lattes Platform in the area of Information Sciences. Currently, the Lattes Platform has 6.1 million resumes from researchers and represents one of the most relevant and recognized scientific repositories worldwide. Through this study, it is possible to understand which attributes of the nodes make them closer to each other, and therefore have a greater chance of creating a connection between them in the future. This work is extremely relevant because it uses a data set that has been little used in previous studies. Through the results it will be possible to establish the evolution of the network of scientific collaborations of researchers at national level, thus helping the development agencies in the selection of future outstanding researchers.
Authors: Felipe Affonso (Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG)), Thiago Dias (Centro Federal de Educação Tecnológica de Minas Gerais (CEFET)), Monique Santiago (Centro Federal de Educação Tecnológica de Minas Gerais (CEFET)),
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Lunch 12:30 - 13:30

Session 3 13:30 - 14:30

Session chair: Mario Antonio Ribeiro Dantas (20 minutes for presentation and 5-10 minutes for questions)
16:30 - 17:00
Concepts in Topics. Using Word Embeddings to leverage the outcomes of Topic Modeling for the exploration of digitized archival collections.

Within the field of Digital Humanities, unsupervised machine learning techniques such as topic modeling have gained a lot of attention over the last years to explore vast volumes of non-structured textual data. Even if this technique is useful to capture recurring themes across document sets which have no metadata, the interpretation of topics has been consistently highlighted in the literature as problematic. This paper proposes a novel method based on Word Embeddings to facilitate the interpretation of terms which constituted a topic, allowing to discern the different concepts "hidden" in one topic. In order to demonstrate this method, the paper uses the "Cabinet Papers" held and digitised by the The National Archives (TNA) of the United Kingdom (UK). After a discussion of our results, based on coherence measures, we provide details of how we can linguistically interpret these results.
Authors: Mathias Coeckelbergs (Université libre de Bruxelles), Seth Hooland (Université libre de Bruxelles),
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17:00 - 17:30
A methodology for creating a well-trained text corpus to enhance Named-Entity Recognition in Portuguese language

Named Entity Recognition (NER) plays an important role on broad natural language processing applicability. According to the literature, the NER process applied to the English language reaches around 90% of accuracy. However, when applied to Portuguese, this accuracy is at most 80%. A wide range of algorithms based on LSTM (Long-Short Term Memory) architecture has being proposed to enhance the NER accuracy. However, a key component to a successful information extraction is the corpora used for NER training. In order to improve the NER in Portuguese language, this paper proposes a methodology for training text corpus based on Portuguese-language journalistic corpora. The Journalistic language has the best adherence to the contemporaneity of the language, since it preserves features such as objectivity, simplicity, impartiality, and is a reference of transmitting the information without ambiguity. The proposed methodology provides a model to extract entities and assess the obtained results with the use of Recurrent Neural Network architectures. At the best of our knowledge, with the proposed methodology, the NER task applied to the Portuguese language overcomes the average accuracy found in the literature, increased from 80% to 85.64%. Moreover, the use of this methodology could decrease the computational costs related to the NER processing tasks.
Authors: Gustavo DE ARAUJO (UFSC), Rogério Silva (UFSC), Luana da Silva (UFSC), Moisés Dutra (UFSC),
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17:30 - 18:00
A distributed tool for online identification of communities in co-authorship networks at a university

Most universities have their public repositories of scientific publications available online. The data is made available raw or by department listing and does not provide the network of co-authorships that implicitly emerges from scientific collaborations among different departments. Sometimes, the net-work of co-authorships is computed within the institution, via standalone applications that have few or no functionalities to explore the structure of collaborations. However, the possibility of searching online and managing the network of scientific communities in the institution is a matter of man-agement efficiency, both for the institution itself and other external collabo-rators. This paper explains a distributed architecture and a tool that uses data from an online institutional repository. The tool calculates and puts available online the co-authorship network that identifies research communities ac-cording to different algorithms. The tool reflects and identifies the emergent structure of communities, graphically analyses communities, exports, reports and follows up with the evolution of communities in time.
Authors: Nuno David (ISCTE-IUL), David Rodrigues (ISCTE-IUL), Maria João Cortinhal (ISCTE-IUL),
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Best paper announcement 14:30 - 14:40

Session 4 14:40 - 15:40

Session Chair: Gustavo Medeiros de Araújo (20 minutes for presentation and 5-10 minutes for questions)
11:30 - 12:00
Examining the Linking Patterns and Link Building Strategies of Mainstream and Alternative Online News Media in Central Europe

The presence of external links or sources in the articles is one of the indicators for assessing their quality. In this article, we explore linking patterns of the most popular traditional and “alternative” digital news media in two V4 countries of middle Europe: Czech and Slovak Republic. Alternative news media are understood as media that protest against traditional or mainstream media. Fake news as articles containing disinformation can appear in traditional media (e.g. in tabloids) as well as in alternative media. Eighteen most popular news media and fifteen most popular alternative media in Slovakia and Czech Republic were selected for quantitative and qualitative analysis of links. With this method, more than 171 million of unique domains of hyperlinks from and to the selected online media were collected and analyzed. The argument to conduct this type of research is that alternative news media are gaining popularity in the countries of Middle Europe and the linking patterns of these media were rarely examined or compared with traditional media. Quantitative analysis and visualization of hyperlinks was performed using two software systems: Ahrefs and Gephi. We concluded that there are some differences between the linking patterns of mainstream and alternative digital news media that need the research attention not only to follow the communication patterns of digital media, but also to be able to detect the type of the news media automatically.
Authors: Andrea Hrckova (Slovak University of Technology in Bratislava), Robert Moro (Slovak University of Technology in Bratislava), Ivan Srba (Slovak University of Technology in Bratislava), Prof. Maria Bielikova (Slovak University of Technology in Bratislava),
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12:30 - 12:30
An altmetric alternative for measuring the impact of university institutional repositories’ grey literature

To obtain licensing, universities must meet a series of standards to guarantee the education of their students; this involves the installation and maintenance of an institutional repository to publish their grey literature. This research aims to find an alternative altmetric tool to measure the impact of such literature. To this aim, we have worked on the customization and optimization of the institutional repository, the creation of procedures to retrieve records, transform and load altmetric data in a new database and the subsequent building of a dashboard-type tool using the altmetric data of the institutional repository’s grey literature. Now there is an alternative to measure the altmetric indices from differ-ent dimensions and analysis perspectives, which makes it possible to take the necessary measures to apply strategies which aim to increase the visibility of the repository. The implementation of the tool in the case study allowed the monitoring and control of the altmetric indices of the institutional repository.
Authors: Miguel Valles (Universidad Nacional de San Martín - Tarapoto), Richard Injante (Universidad Nacional de San Martín - Tarapoto), Edwin Hernandez (Universidad Nacional de San Martín - Tarapoto), Juan Riascos (Universidad Nacional de San Martín - Tarapoto), Marco Galvez (Universidad Nacional de San Martín - Tarapoto), Juan Velasco (Universidad Nacional de San Martín - Tarapoto),
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12:30 - 13:00
Proposal of model for curation digital objects of a oncology research center

This article presents a proposal model for curation of digital objects from an oncology research center in Santa Catarina State. This is an exploratory research with a qualitative approach, in which the technical procedure of case study was used. From the case study it was possible to know the digital objects that make up the informational context, and the actions taken of digital curation in the studied cancer research center. The basal phases that make up the proposed model were extracted from the literature. As a result of it, there is a model proposal to support the preservation, maintenance, access optimization, use, reuse, and the promotion of added value to the digital objects of the studied cancer research center.
Authors: Josiane Mello (Federal University of Santa Catarina, Brazil), Angel Godoy Viera (Federal University of Santa Catarina, Brazil),
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Break 15:40 - 16:00

Session 5 16:00 - 17:00

Session Chair: Enrique Muriel Torrado (20 minutes for presentation and 5-10 minutes for questions)
14:30 - 15:00
Identification of the relationships between the stages of the Data Lifecycle and the principles of the General Data Protection Act

The purpose of this paper is to present an analysis of the relationships between the principles of the General Data Protection Act - LGPD and the stages of the data life cycle. For the identification of relations, the following question was sought to be answered: What is the relationship between each LGPD principle and each of the stages of the data lifecycle? Based on the results, it was possible to observe that the data life cycle model can be used to support the law compliance activities, since the law principles presented relations with the model stages. It was also observed that the principles of adequacy of data processing for the purposes of use and transparency are those that guide the other principles and that, besides these, the principles of safety, prevention, responsability and accountability recommended by law, were related with all phases of the data life cycle.
Authors: Gislaine Freund (Universidade Federal de Santa Catarina - PPGCIN/UFSC), Priscila Fagundes (Universidade Federal de Santa Catarina - PPGCIN/UFSC), Douglas Macedo (Universidade Federal de Santa Catarina - PPGCIN/UFSC),
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15:00 - 15:30
Organizational Learning in the Age of Data

In information-driven economy, few organizational competencies are as important as the capability to systematically capture, synthesize and disseminate throughout the organization competitively advantageous decision-guiding knowledge. Traditionally, organizational learning has been viewed as a human-centric endeavor, but the rise of big data and advanced data analytic technologies are compelling a fundamental reconceptualization of the scope and modalities of organizational learning.
Authors: Andrew Banasiewicz (Cambridge College, Boston MA 02129, USA),
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15:30 - 16:00
Provenance Data Collection Method Proposal for Application in Hemotherapy Centers in Brazil

Storing data on anemia indices using Data Provenance was one aspect of the overall purpose of this paper, where it focused on developing a Provenance Data collection method based on the Provenance Data Model (PROV-DM) as a proposal for application in a Hemotherapy Center in Brazil. For the development of the method were used concepts of Data Provenance, Provenance of Knowledge and techniques of scientific workflows in the use of computational tools, characterizing an exploratory research, of practical and deductive nature, with application of experiment (case study). Those who were unsuitable for blood donations who had favorable anemia rates to be rejected for donations were quantified and analyzed. The method was developed in a real-world setting, with actual data extracted specifically from the reports generated by the system of a Brazilian Hemotherapy Center, provided from 2000 to 2018. Of the 197,551 blood donor candidates who presented to the Hemotherapy Center in a 19-year study, it was possible, after analysis, to quantify the unfit candidates with the highest anemia index. There were 1,011 male candidates, totaling 4.02% of candidates unfit for blood donation. Females were 4.039 candidates with anemia rates, totaling 16.09% of donors unfit for blood donations.
Authors: Márcio José Sembay (Federal University of Santa Catarina), Douglas Dyllon Macedo (Federal University of Santa Catarina), Moisés Dutra (Federal University of Santa Catarina),
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Session 6 17:00 - 18:00

Session chair: Carlos Luis González Valiente (20 minutes for presentation and 5-10 minutes for questions)
16:30 - 17:00
Personal data protection and its reflexes on the data broker industry

Demonstrates the relationship between government and private interests in identi-fying people’s profiles on the Internet. Describes the establishment and develop-ment of information aggregators and merchants, the data brokers. Discusses the boundaries of personal data commoditization, which in consequence wears away privacy and anonymity. Associates the inception of laws that mandate publicity to data breaches events, exposing the model, and ensuing debates on the need of further regulation. Presents the innovative generation of legislation created to govern a business that up until then operated free from public scrutiny. Introduc-es ideas to prevent the extinction of such business model upon the shift to privacy and data protection.
Authors: Guilherme Birckan (UFSC), Angel Godoy Viera (UFSC), Douglas Jeronimo de Macedo (UFSC), Moises Lima Dutra (UFSC),
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17:00 - 17:30
Intellectual Authorities and Hubs of Green Chemistry

Green Chemistry (GC) is an answer to the problems ensuing from chemical pollution, adopting a proactive, prevention-based stance. After nearly three decades of its coming into being, the advances in the field towards groundbreaking chemical practice are still under discussion and new research is needed in order to systematize existing knowledge and to point to efficient means to select information. Our purpose with this study is to broaden the understanding on GC research structure, by pointing the researchers that have most contributed to its growth, spread and consolidation (its intellectual hubs), and the authors upon whose knowledge they have drawn (intellectual authorities). We analyzed 14,142 documents either containing the term “green chemistry” or published in Green Chemistry and Green Chemistry Letters and Reviews between 1990 and 2017, using network analysis and co-citation analysis. Fourteen hubs were found, and twenty-one intellectual authorities, distributed along six big specialties, previously described in the literature. Results corroborate previous analyses of the field, but this research has the advantage of stemming from the dynamics of scientific production, rather than from previously defined qualitative categories of the field itself.
Authors: Leonardo Marcelino (Universidade Federal de Santa Catarina), Adilson Pinto (Universidade Federal de Santa Catarina), Carlos Marques (Universidade Federal de Santa Catarina),
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17:30 - 18:00
Librarianship in the age of data science: data librarianship Venn diagram

A Venn diagram is used in mathematics to graphically symbolise properties, axioms, and problems concerning sets and their theories. Thus, this study applied a Venn diagram to describe a new background for data librarianship as a field relating to information science, e-science, and data science. Data librarianship is a new discipline that is located within the thematic core of the triad—information science, e-science, and data science. The first set on the proposed Venn diagram is information science. Information technology concepts are fundamental to the comprehension of data librarianship in the context of information science. The second set is e-science, an innovative field that incorporates technical tools and devices that have been built by contemporary technology into science. The third set is data science, a way of representing data-driven research in the most diverse knowledge fields, and a combination of data analysis and development of new products and services based on data; it is a set of the skills, methods, techniques, and technologies of statistics and computer science used to extract knowledge and to create new products and services from data. To ensure greater comprehension of data librarianship, a relatively new field, we suggest some reading materials. The formal discipline of data librarianship is yet to be established in many countries across the globe. Thus, there is the lack of adequate information and certification on data librarianship.
Authors: Alexandre Semeler (Geosciences Institute, Federal University of Rio Grande do Sul), Adilson Pinto (PGCIN, Federal University of Santa Catarina),
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Closing 18:00 - 18:10