Complete Program (with abstracts)
- Opening - Workshop Introduction
- Minute of madness – Oral presentation of posters
08:30-09:30 - Session 1 - Urban mobility
- Characterizing the client usage pattern and the service demand of a two-way car sharing system
o Authors: Felipe Rooke Da Silva, Alex Borges Vieira, Jussara M. Almeida, Idilio Drago and Victor Aquiles
o Abstract: Urban mobility is directly linked to the demand for communication resources and, clearly, its understanding is useful for a better communication planning. However, getting data about urban mobility is still a challenge. In many cases, only a few companies have access to accurate and actual data. In most cases, these data are privacy sensitive. In this way, it is important to generate models that can represent urban mobility patterns and their social interactions. In this paper, we characterize and model urban mobility, from the steering point of a two-way carsharing system. We explore public data of Modo, a carsharing system that operates in Vancouver (Canada) and nearby regions. Our study leverage information about the habits and driving styles of such service that can be explored for urban and communication networks planning.
- MobilityMirror: Bias-Adjusted Synthetic Transportation Datasets
o Authors: Luke Rodriguez, Babak Salimi, Haoyue Ping, Julia Stoyanovich and Bill Howe.
o Abstract: We describe customized synthetic datasets for publishing mobility data. Private companies are providing new transportation modalities, and their data is of high value for integrative transportation research, policy enforcement, and public accountability. However, these companies are disincentivized from sharing data not only to protect the privacy of individuals (drivers and/or passengers), but also to protect their own competitive advantage. Moreover, demographic biases arising from how the services are delivered may be amplified if released data is used in other contexts. We describe a model and algorithm for releasing origin-destination histograms that removes selected biases in the data using causality-based methods. We compute the origin-destination histogram of the original dataset then adjust the counts to remove undesirable causal relationships that can lead to discrimination or violate contractual obligations with data owners. We evaluate the utility of the algorithm on real data from a dockless bike share program in Seattle and taxi data in New York, and show that these adjusted transportation datasets can retain utility while removing bias in the underlying data.
- MODAL - A Platform for Mobility Analyses Using Open Datasets
o Authors: Wender Zacarias Xavier and Humberto Torres Marques Neto.
o Abstract: Cities are becoming smart environments with the use of information and communication technologies (ICT). Data from these technologies are stored by various devices spread throughout the city and are available in open data portals, which can be used to improve essential services such as public transport and fed into platforms for visualization and analyses. Human and urban mobility analyses demonstrate that understanding movement patterns can assist governments in city's decision-making process, as well as improve life quality of citizens. Aiming to enable mobility analysis in different cities, this work presents MODAL platform. This platform replicates mobility analyses and algorithms on databases of different cities using data obtained from open data portals. We assess the platform with a case study performing analyses of the transportation displacement within three different cities using complex network metrics. The results demonstrated the public transportation system efficiency showing regions of Chicago, Dubai and Taichung well served and regions which are key points to the transportation city interconnecting various areas. Moreover, we could evaluate how improved the transportation system would be by adding new lines or new transport system. The analyses demonstrated the platform potential to be used as support decision system for governments, showing the possibility of applying open data to improve city services and facilitate the conduction of analyses on various cities.
09:30-10:30 - Session 2 – Urban sensoring
- Mensageria: A Smart City Framework for Real-time Analysis of Traffic Data Streams
o Authors: Sergio Lifschitz, Rafael Pereira De Oliveira, Markus Endler, Marcos Roriz and Felipe Oliveira Carvalho.
o Abstract: Several smart city systems have focused on addressing a specific mobility problem scenario (e.g. air pollution, traffic jam) in a given city. The task of adding, extending, or porting the smart city scenario to other cities can be very challenging due to the rigid structure of such existing systems. To address this issue, in this paper we investigate common programming constructors that can be used to leverage the construction of such dynamic, smart city systems in the mobility domain. We propose Mensageria, a framework based on both the Complex Event Processing data-streaming processing paradigm and relational database management systems, which can dynamically deploy new or extend existing smart city scenarios in near real-time and maintain an updated dataset for provenance purposes. Mensageria provides several real-time primitives, such as filter, join, and enrich, that can be used to integrate, process, and analyze the city entities data streams. We discuss the generality, performance, and limitations of the proposed constructs through a real-world case study that was used in the Olympic Games of Rio in 2016 to detect, in real-time, existing and new situations that could affect the city mobility infrastructure.
- SLEDS: A DSL for Data-Centric Storage on Wireless Sensor Networks
o Authors: Marcos Aurélio Carrero, Martin A. Musicante, Aldri Luiz Dos Santos and Carmem Satie Hara.
o Abstract: The dynamicity requirements of urban sensor networks rise new challenges to the development of data management and storage models. Software component techniques allow developers to build a software system from reusable, existing components sharing a common interface. Moreover, the development of urban sensor networks applications would greatly benefit from the existence of a dedicated programming environment. This paper proposes SLEDS, a Domain-Specific Language for Data-Centric Storage on Wireless Sensor Networks. The language includes high-level composition primitives, to promote a flexible coordination execution flow and interaction between components. We present the language specification as well as a case study of data storage coordination on sensor networks. The current specification of the language generates code for the NS-2 simulation environment. The case study shows that the language implements a flexible model, which is general enough to be used on a wide variety of sensor network applications.
- Extraction and Exploration of Business Categories Signatures
o Authors: Leonardo Da Silva and Thiago Silva.
o Abstract: In order to offer smarter urban services, it is fundamental to understand properly a target urban phenomenon, for instance, businesses functioning dynamics, i.e, their popularity times. Different business types may have distinct popularity times that can be dictated not only by the service offered but also due to diverse economic, social and cultural aspects. Performing the business popularity time comprehension allows us, for instance, to use this information as a business descriptor that could be explored in new services. Recently, Google launched a service, namely Popular Times, which provides the popularity times of commercial establishments. In this study, we collected and analyzed a large-scale dataset provided by that service for business related to consumption of food and beverage in different cities in Brazil and in the United States. Our main contributions are: (1) clustering and analysis of the collected business popularity times dataset in each studied city; (2) approach for identifying the signature that represents the behavior of certain categories of venues; (3) training and evaluation of an inference model for categories of establishments; (4) user evaluation of some of our results.
10:30-11:00 - Coffee Break – Poster session (odd numbers)
- 1. Using Multilayer Social Networks in an Analysis of Higher Education for Professional Demand
o Authors: Rodrigo Campos, Rodrigo Pereira Dos Santos and Jonice Oliveira.
o Abstract: Authorization to open undergraduate courses in major cities considers the quality of physical facilities, faculty, and organization of institutions. An important factor for the process of opening courses is the region economic factor. Considering the regional labor market for such planning can bring benefits and interconnecting these elements transforms cities into smart cities. However, although there are several big data sources that provide this information, there is still an individualistic data view. Therefore, this work proposes to interconnect these factors with the multilayer social networks resources to support the decisions of higher education and their relations with the professional demands. To do so, an experiment is carried out to relate data from higher education offerings and employment/unemployment rates, creating a multilayer graph from these unstructured da-ta. Our contribution is the investigation on how non-structured data can be analyzed in a multilayer perspective for this domain and how to assign proportional weights to the nodes in order to generate weighted graphs.
- 3. Strategy for Generation of Knowledge through Automatic Correlation of Dimensional Data in Star Schema: Application in the Context of Leishmaniasis
o Authors: Wallace Pinheiro, Geraldo Xexeo, Jano Souza, Ana Bárbara Pinheiro and Ciro Gomes.
o Abstract: The aim of this article is to propose a methodology for generation of knowledge through correlation techniques, based on dimensional data obeying a star model. This methodology relates and integrates data from one or more thematic areas (data marts) using correlation coefficients applied to data derived from facts and dimensions of a data mart. In order to analyze the application of the strategy, we selected the database of Notification of Diseases and Injuries Information System (SINAN) of Departament of Health to gather information about a particular neglected disease that affects several Brazilian capitals: Visceral Leishmaniasis. The proposed methodology has generated several correlations that can support the planning of public strategies to combat this disease.
- 5. An analysis of the network of rural producers in the state of Rio de Janeiro
o Authors: Emanuele Nunes de Lima Figueiredo Jorge, Claudio Miceli de Farias, Igor Leão Dos Santos and Mario Sergio de Souza Pereira.
o Abstract: The unexpected growth of the world population and the exodus from rural areas to the city lead to a food insecurity concern. Recently, a strike of truck drivers caused significant impacts on the distribution of food in the city of Rio de Janeiro and other cities in the country. To address the food insecurity problem, solutions guided by the Internet of Things paradigm such as smart farms have been gaining increasing attention. However, food production in smart farms is still a challenge. To surpass this challenge, a possible solution is to map the information regarding the producers of the state of Rio de Janeiro, and analyze this data together with other sources, reducing the difficulties in the distribution of food products, and allowing information exchange, for the development of sustainable cultivation. In this paper, a small analysis of the producers of the state of Rio de Janeiro is presented. We then present an initial monitoring system that would allow a big data analysis in the future. These analyzes are implemented based on environmental data (temperature, humidity, light intensity) that are related to the growth of these producers' crops.
- 7. Data Quality assessment and enhancement on Social and Sensor Data
o Authors: Gabriel Rodrigues Caldas de Aquino, Claudio Miceli de Farias and Luci Pirmez.
o Abstract: Smartphones are key devices in the Internet of Things paradigm. Social networking services on the Internet can use smartphones applications as data providers. The data gathered from sensors and data harvested from social networking services can be used by different applications for providing context-aware services. However, the excellence of the data-oriented services depends on the Data quality (DQ). DQ is critical for decision making mechanisms. We present the problem related to DQ when dealing with social and sensor data. Also, we present and explore a framework whose objective is to evaluate and control DQ aspects when dealing with social and sensor data.
- 9. Is the location of Public Health Units in Curitiba meeting the citizen's needs?
o Authors: Filipe Lautert, Tatiane Lautert, Nadia P. Kozievitch and Luiz Gomes-Jr.
o Abstract: Guaranteeing adequate health services to the population is a challenge, especially in developing countries where limited resources must be optimized in order to reach a larger portion of the population. To properly assess the adequacy of health services and prioritize new investments, it is important to gather a large amount of relevant data, integrated from various sources. This paper presents an ongoing research focusing on Curitiba, one of the largest cities in Brazil. We have aggregated socio-political, geographical, transportation and health data from open repositories in order to understand the dynamics of how citizens choose their health units when required, as well as verify the availability of bus stops close to these units. The paper reports findings from our exploratory analysis, highlighting the cases where the city's administration is on the right track, but also the areas which require more investment. More specifically, using GIS and Data Analysis tools we analyze the occurrence of medical appointments made outside of the citizens’ residential neighborhood and the most frequent diseases they had. We also detail which health units do not have a bus stop in a determined radius.
- 11. The Role of Social Capital in Information Diffusion over Twitter: a Study Case over Brazilian posts
o Authors: Hercules Sandim, Danilo Azevedo, Ana Paula Couto Da Silva and Mirella M. Moro.
o Abstract: Social Capital is the resulting advantage of the individual's localization in a social structure. It can be measured by traditional complex networks metrics, or specific ones, such as information capital, brokerage and bridging. Our goal is to verify which users have high information capital, bridging and brokerage for providing and spreading information. To do so, we first categorize Twitter users into seven types: typical users, primary media, secondary media, independent experts, fan accounts, fake accounts and potential bots. Then, we analyze their profiles on trending topics. Our results show potential bots and fan accounts as the main information spreaders in Brazil, a very concerning result given the upcoming presidential election in October 2018.
- 13. Analyzing polarization in Twitter: The murder of Brazilian councilwoman and activist Marielle Franco
o Authors: Livia Ruback and Jonice Oliveira.
o Abstract: Social media has allowed people to publicly express, at near zero cost, their opinions and emotions on a wide range of topics. This recent scenario allows the analysis of social media platforms to several purposes, such as predicting elections, exploiting influential users or understanding the polarization of public opinion on polemic topics. In this work, we analyze the Brazilian public perception related to the murder of a Rio councilwoman, Marielle Franco, member of a left-wing party and human-rights activist. We propose a polarity score to capture whether the tweet is positive or negative and then we analyze the score evolution over the time, after the murder. Finally, we evaluate our approach correlating the polarity score with human judgment over a randomly sampled set of tweets. Our preliminary results show how to measure polarity on public opinion using a weighted dictionary and how it changes over time
- 15. Case Study: Zooming in on NYC Taxi Data with Portal
o Authors: Julia Stoyanovich, Matthew Gilbride and Vera Moffitt.
o Abstract: In this paper we develop a methodology for analyzing transportation data at different levels of temporal and geographic granularity, and apply our methodology to the TLC Trip Record Dataset, made publicly available by the NYC Taxi and Limousine Commission. This data is naturally represented by a set of trajectories, annotated with time and with additional information such as passenger count and cost. We analyze TLC data to identify hotspots, which point to lack of convenient public transportation options, and popular routes, which motivate ride-sharing solutions or addition of a bus route. Our methodology is based on using an open-source system called Portal that supports an algebraic query language for analyzing evolving property graphs. Portal is implemented as an Apache Spark library and is inter-operable with other Spark libraries like SparkSQL, which we also use in our analysis.
11:00-12:30 – Keynote: Landscape of Practical Blockchain Systems and Their Applications
- Keynote Speaker: Dr. C. Mohan (IBM Almaden Research Center & Tsinghua University)
- Abstract: The concept of a distributed ledger was invented as the underlying technology of the public or permissionless Bitcoin cryptocurrency network. But the adoption and further adaptation of it for use in the private or permissioned environments is what I consider to be of practical consequence and hence only such private blockchain systems will be the focus of this talk. Computer companies like IBM, Intel, Oracle, Baidu and Microsoft, and many key players in different vertical industry segments have recognized the applicability of blockchains in environments other than cryptocurrencies. IBM did some pioneering work by architecting and implementing Fabric, and then open sourcing it. Now Fabric is being enhanced via the Hyperledger Consortium (part of The Linux Foundation). A few other systems include Enterprise Ethereum, Sawtooth and R3 Corda. While currently there is no standard in the private blockchain space, all the ongoing developments involve some combination of database, transaction, encryption, virtualization, consensus and other distributed systems technologies. Some of the application areas in which blockchain pilots are being carried out are: smart contracts, derivatives processing, e-governance, Know Your Customer (KYC), healthcare, supply chain management and provenance management. Many production deployments are also operational now. In this talk, which is intended for both technical and non-technical audiences, I will describe some use-case scenarios, especially those in production deployment. I will also survey the landscape of private blockchain systems with respect to their architectures in general and their approaches to some specific technical areas. I will also discuss some of the opportunities that exist, and the technical and organizational challenges that need to be addressed. Since most of the blockchain efforts are still in a nascent state, the time is right for mainstream database and distributed systems researchers and practitioners to get more deeply involved to focus on the numerous open problems. My extensive blockchain related collateral can be found at http://bit.ly/CMbcDB
12:30-02:00 (pm) - Lunch break
02:00-03:30 – Panel: Social Computing for Smarter Cities
- Panelists: Bill Howe (University of Washington), Elaine Rabello (FIOCRUZ and Universidade do Estado do Rio de Janeiro), Gabriela Ruberg (Central Bank of Brazil), and Sihem Amer-Yahia (Laboratoire d'Informatique de Grenoble)
- Moderator: Mirella Moro (Universidade Federal de Minas Gerais)
03:30-04:00 - Coffee Break – Poster session (even numbers)
- 2. Optimization of urban semaphore times turning into JSSP
o Authors: Antonio M R Almeida, Jose A F Macedo and Javam C Machado.
o Abstract: The objective of this paper is to cover the research in the area of adaptive traffic control with emphasis on applied optimization methods. A distinction can be made between classical systems, which operate with a common cycle time, and the more flexible ones, phase-based approaches, which are shown to be more suitable for adaptive traffic control. Classic optimization solutions for this problem result in a model which is relatively easy to represent but may be difficult to fit into the standard mixed-integer programming (MIP) scheme. We propose an alternative approach to find an optimal global solution for the green wave problem on hot routes, which consists of reducing it to a Job Shop Scheduler problem using the Webster Model to adapt the cycles to road characteristics and average traffic speed.
- 4. Computer-assisted city touring for explorers
o Authors: Gabriel Spadon and Jose Fernando Rodrigues Jr..
o Abstract: The basic purpose of a map is to trace shortest paths between two locations in a city. However, this is not always what a user needs. Consider a tourist in an unknown city, he/she might want to trace routes to visit multiple landmarks while passing through the main streets of the city, possibly more than once through the same street. Such functionality is not yet available in online map services, which are prone to provide shortest paths that connect all landmarks. Rather, is of common interest a tour that puts together the most central streets (topologically speaking), minimizes the trajectory and, at the same time, passes through such landmarks. To cope with this problem, it is possible to investigate techniques of Center-Piece Subgraph, Absorbing Random Walk Centrality and Spanning Edge-Betweenness; such techniques can be used to find induced subgraphs that optimize centrality measures for a set of referential nodes or edges, i.e. landmarks or streets. The results shall be in the form of optimized algorithms, and how to integrate them into online systems. Studies in this line can succeed if they can guarantee timely scalability at the same time that they provide algorithms that produce tours (1) considering all the known destinations; (2) including the main streets of a city; and, (3) ensuring the shortest routes.
- 6. Multi-criteria Analysis applied to the inspection of Aedes Aegypti mosquito breeding places
o Authors: Yuri Lima, Wallace Pinheiro, Carlos Eduardo Barbosa, Sérgio Rodrigues, Jano Souza, Jacson Hwang, Pedro Henrique Bruno, Eduardo Cesar Gomes, Miriam Chaves and Geraldo Xexéo.
o Abstract: Aedes Aegypti is a vector for the transmission of several diseases such as Dengue fever, Chikungunya, Zika fever, and yellow fever. In 2016, over one million of cases of these diseases were reported in Brazil, an alarming public health issue. One of the ways of controlling the disease is by inspecting and neutralizing the places where the Aedes Aegypti lays its eggs. The SIGELU Aedes is a system developed by the Brazilian Ministry of Planning, Development, and Administration and LEMOBS to support such effort. In this work, we propose a multi-criteria analysis to create a geolocated indicator of the inspections reported through the system. We apply the proposed analysis to a database of inspections in government buildings to test our proposition by generating a heat map allowing us to draw some conclusions and propose future works.
- 8. Applying a Social Network Perspective to Identify Social and Technological Aspects in the Startup Ecosystems of State of Rio de Janeiro
o Authors: Kesia Olimpio Braga Mamede, Rafael Elias De Lima Escalfoni and Jonice Oliveira.
o Abstract: Startups ecosystems are important innovation drivers, responsible for job creation and revenue generation. These entrepreneurial communities work promoting technological development through partnerships among entrepreneurs, universities, support agencies and industries. These complex relationships are crucial to ensure the access to the means that enable projects, such as technologies, know-how, infrastructure and funding. Understanding which characteristics are inherent to the community, it is possible perform a better integration and improve the efficiency in the network. This paper presents a map of startup ecosystem of Rio de Janeiro state, exhibiting technical and social aspects of this entrepreneurial community. In our approach, the technical information was extracted from the ReINC database (Network of Promoters of Innovative Enterprises). Then, the professional social data from entrepreneurs and others involved were collected from the social media LinkedIn. After crossing data extracted from official databases and social media, we identified some crucial aspects to ecosystems’ development using social network analysis.
- 10. Checking fake news on web browsers: an approach using collaborative datasets
o Authors: Anderson Cordeiro and Jonice Oliveira.
o Abstract: Rumors are a constant reality related to information sharing on social networks. The increase of interactions, encouraged by social media, facilitates the dissemination of non-validated content. Sometimes, promoting misinformation and causing irreparable damages. The dynamism of online activities transforms the process of evaluating the accuracy of a message in a lonely task, user-dependent and often tricky. The lack of reliable and centralized data sources that can be used as a reference for content verification, as well as the lack of tools to support this process, makes it harder to verify facts quickly. This article presents the creation of a collaborative dataset of fake Brazilian news, an API to enable the validation of contents and how this environment was used in the development of an extension for the Google Chrome browser, giving rise to a solution that allows checking a text selected by the user.
- 12. Heimdall - Internet of Things (IoT) Platform for Data Retrieval
o Authors: Gabriel Martins de Oliveira Costa, Marcos Araujo, Tiago Cruz De França Cruz de França and Claudio Miceli de Farias.
o Abstract: The emergence of the Internet of Things paradigm fuel the discussion of how urban environments will benefit from applications of the IoT domain, to name a few, smart grids, smart vertical farm and healthcare applications. Domains likewise vertical smart farm are envisioned to share the same space as people and machines even if humidity and temperature conditions required to grow plants are not ideal to systems room, nor to workplaces, which make the design of these environments even more challenging. Under this point of view more complex concepts likewise Smart Ecosystems (Smart cities, Smart agriculture and Industry 4.0) flourished. Heimdall is a microservices platform that aim to provide comprehensive services allowing users to storage and visualize data streams gathered by IoT systems. Built to explore Continuous Integration tools, Heimdall is envision to run a flexible and powerful infrastructure able to manage elastic resource provisioning in a cloud computing environment design to power Smart Ecosystems.
- 14. Publish or Post: Identification of influences between science and society through intelligent systems
o Authors: Diogo Nolasco and Jonice Oliveira.
o Abstract. Every social community is deeply influenced by scientific discoveries and technology. Research results have impacted our lives directly, such as the cure of diseases and the development of new devices. The interrelationship of the academy and society remains a mystery, despite these influences. How scientific works impact and are recognized by society? Do research works match societal demands? Trying to answer these questions, we create a system that is capable of generating links between scientific and social data. We use the scientific articles as “science sensors” and online social networks as “social sensors”. Topic modeling algorithms enable us to detect and to link main research themes and social events. The proposed system uses heterogeneous sources and can be applied in a variety of scenarios. We evaluate our environment in the Zika domain, using a large-scale Twitter corpus combined with PubMed articles. Our approach detected links among various subevents, suggesting that some degree of the scientific impacts in society can be automatically inferred. Results can open new opportunities for identifying the social consequences and reactions produced by scientific discoveries.
- 16. Challenges and Opportunities of Social Computing in Urban Agriculture in Global North and South Countries
o Authors: Sergio Serra, Pedro Vieira Cruz and Ana Claudia Macedo Vieira
o Abstract: The size of the world’s largest cities is increasing; the urbanization process is complicated and different in developed and developing countries. However, if well managed, urban spaces may offer valuable opportunities for economic and social development. This vision paper investigates the current challenges and opportunities in Urban Agriculture (UA) and discusses if the adoption of Urban Computing (UC) and Information and communications technologies (ICT) can aid urban dwellers, farmers and planners to progress UA in Global North or Global South countries Like Germany and Brazil.
04:00-05:20 - Session 3 and 4
- Session 3 – Contemporary Social Problems
o Comparing emotional reactions to terrorism events on Twitter
§ Authors: Jonathas Gabriel Dipp Harb, Karin Becker.
§ Abstract: Over the last years, terrorism attempts have threatened the global population safety, impacting people in a complex emotional way. In this paper, we apply deep learning techniques to classify emotions of terrorism events, and develop a comparative analysis about emotional reactions on four events based on the demographics of tweeters, particularly gender, age and location. Our research questions involve comparing these events in terms of emotional shift, emotions according to age and gender, emotional reaction according to the closeness of the event and number/type of victims, as well as the terms used to express emotional reactions. The main conclusions were: fear, anger and sadness are the most expressed emotions; the emotions expressed are directly related to gender (fear for women, and anger for men); emotions are not related to the closeness of the events, but seem to be acted by the casualties (number of kills/injuries); tweeters expressing fear and sadness tend to regard themselves as potential victims, sharing words of aection and support, while tweeters expressing anger tend to use intense words of hate, intolerance and anger.
o Using government data to uncover political power and influence of contemporary slavery agents in Brazil
§ Authors: Leticia Dias Verona, Giseli Lopes and Maria Luiza Machado Campos.
§ Abstract: This work uses open data published by the Brazilian government to investigate connections between agents involved on contemporary slavery labor and politicians, evaluating their power and influence. A network was built on data from Brazilian elections and campaign donations since 2002, including all candidates and donors associated to slave labor. Not only 263 direct candidatures from slavery agents were identified, but also more than 40 million Brazilian Reais in campaign donations for candidates for all electoral positions, showing a strong relation between slavery agents and Brazilian politicians. Data were also analyzed using metrics based on sociologist Manuel Castells' Network Theory of Power that measure how much power and influence each donation is accounted for, in addition to its absolute amount. The resulting network was semantically enriched and modeled according to existing ontologies and published using Linked Open Data standards in a semantic knowledge graph, allowing information to be identified, disambiguated and interconnected by software agents in future research.
- Session 4 – Collaboration and Crowdsourcing
o CidadeSocial: an application to support the exchange of information among citizens
§ Authors: Ana Clara Correa, Eliel Roger, Tiago Cruz França, José Orlando Gomes and Jonice Oliveira.
§ Abstract: The combination between mobile devices and easy access to the Internet improves the spread of information produced by human beings in their daily lives. People share all type of information in urban spaces such as events, opinions and problems. They act as human sensors monitoring and sharing information about city demands in social media. Moreover, these platforms allow people to support each other - even strangers - through questions answering, recommendations and clues. However, many of that information is lost. Even social media (e.g. Facebook and Twitter) limit the spread of information flow up to the network borders, because their focus is on the relationship network. In this way, the information does not reach the people outside this network. This paper describes an application - named CidadeSociall - that allows citizens to exchange information according to their common interests. The application exploits the user’s geospatial location to create a temporal social network, provides recommendations based on their profile and uses a gamification approach to improve the users’ engagement. That way, we argue that the CidadeSocial is a tool with potential to serve as an interface for citizen engagement in improving the daily life of cities.
o Structures of interactions and data in urban networks: the case of PortoAlegre.cc
§ Authors: Pablo Florentino and Gilberto Corso Pereira.
§ Abstract: Urban spaces have been occupied by the massive use of new information and communication technology as digital social networks and platforms. The digital dimension of cities became a bidirectional and omnipresent path, creating relational and interactional structures able to exchange data and media. In such urban context, this work investigates digital networks structuring paths and exchanges among some of their composing elements. The networked city was analyzed and debated as a complex system that demands research about communicational plurality and development of urban space representation, considering the enlargement of contexts and increasing of informational and communicational density. Digital traces from social networks developed in PortoAlegre.cc, a collaborative web map registering issues and use of urban space, were used as data input for this research. Social network analysis was used as approach that permitted evaluating network structures, comprehending paths among their elements. The results reveal the existence of short paths, with predominance of structures that follow Small World model. The analyzes showed efficient networks for data exchange increasing informational and communicational density. This works contributes for Urban computing bringing alternative approaches and perspectives for this multidisciplinary area with representation and knowledge that enhance the debate about urban space.
o DMEK: Improving Profile Matching in Opportunistic Collaborations
§ Authors: Jose Guilherme Mayworm, Fabricio Firmino, Jonice Oliveira and Claudio De Farias.
§ Abstract: As the number of mobile devices grow, also grows the amount of data exchanged. This amount of data is a problem to Internet Service Providers. A way to find a solution to this problem is to use the mobile devices wireless network capabilities to exchange data forming mobile P2P networks. These networks should opportunistically collaborate to exchange information to other devices in their proximity, only requiring users to specify their interests. This paper presents DMEK (Decision Mobile Exchange of Knowledge) a solution where mobile devices are used to disseminate knowledge among its users in an opportunistic manner using a decision mechanism. Experiments show DMEK feasibility and performance.
05:20-05:30 - Closing Session