BiDU 2018 - Workshop on Big Social Data and Urban Computing

BiDU – Workshop on Big Social Data and Urban Computing
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Friday, August 31, 2018
In conjunction with VLDB 2018
Rio de Janeiro, Brazil
https://sites.google.com/view/bidu2018/
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DESCRIPTION OF THE WORKSHOP’S TOPIC AND ITS GOALS
In urban spaces, there is a huge amount of heterogeneous data being generated by a diversity of sources, such as sensors, devices, vehicles, smart buildings, and others. Although they are used to monitor basic services, they can provide significant information about human interactions and populational dynamics. Moreover, people constantly interact with each other through social media services, and much of interpersonal interaction is nowadays mediated by information technology. Citizens consume and share information about their cities - such as problems, events, ideas, suggestions, criticisms, and demands – acting as ‘human sensors’, forming opinions and participating in the city evolution.
These data explosion has resulted in the emerging topic of “Big Social Data”. Broadly speaking, Big Social Data refers to large data volumes that relate to people or describe their behaviors, needs, and patterns. The volume, the production and spreading velocity, and the variety (providing semantic richness) open enormous possibilities for the usage and analysis of such data for the understanding of urban spaces, tackling the major issues that these localities face, and helping in the creation of smarter and sustainable cities.
This understanding can remedy a wide range of issues affecting the everyday lives of citizens and the long-term health and efficiency of cities. The use of Big Social Data in urban computing helps us to understand the nature of urban phenomena and even predict the future of cities, creating solution to reduce costs and optimize resource consumption, improve population mobility, provide higher human life quality, enhance decision making in emergency scenarios, and connect with citizens for a continuous city planning.
Urban computing is a process of acquisition, treatment, and analysis of big and heterogeneous data to better understand the different types of social interactions in a city among different types of communities and events, in order to identify phenomenas. For instance, the advances in location-acquisition using mobile devices have generated massive spatial trajectory data, which can be use to predict the mobility of a diversity of moving objects, such as people, vehicles and animals. This understanding can remedy a wide range of issues affecting the everyday lives of citizens and the long-term health and efficiency of cities. Big social data management in urban computing enables to understand the nature of urban phenomenas and even prediction in the city. The goal is the the proposal of new solutions to optimize urban ressource consumption and costs (e.g. transport, energy consumption) to improve the quality of population mobility, providing higher quality of life for the citizens. In addition, event prediction can enhance decision making in emergency scenarios, and connect with citizens for a continuous city planning.
Urban computing is an interdisciplinary research field bringing new challenges. This workshop aims to connect contributions related to the usage and management of Big Social Data in multidisciplinary research spanning across computer science - such as engineering, environmental studies, health, urban planning and social sciences - for urban sustainability, transparency, livability, social inclusion, place-making, accessibility, and resilience.
The workshop welcomes contributions describing original ideas, promising new concepts, and practical experience. In particular, we solicit papers of different types:
· Research - Papers proposing new approaches, models, theories or techniques related to Big Social Data and Urban Computing, including new data structures, algorithms, whole systems, and frameworks. They should make substantial theoretical and empirical contributions to the research field.
· Experiments and Case Studies - Papers focusing on the experimental evaluation of existing approaches including data structures and algorithms for Big Social Data and Urban Computing bringing new insights through the analysis of these experiments. Results of experiments and case studies papers, for example, can describe benefits or disadvantages of well-known approaches in new scenarios, opening new research problems and challenges by demonstrating unexpected behavior or phenomena, or comparing a set of traditional approaches in an experimental survey.
· Industry and Application - Papers reporting practical experiences on Big Social Data and Urban Computing. Industry and Application papers might describe specific application domains and detail the solution process.
· Dataset - Papers describing a dataset - completely cleaned, treated, curated, opened and legal - possible to be reused or applied in other scenarios. The final contribution is a dataset available to access and reuse, but the paper must present all the information necessary to understand the processes of data gathering and treatment, and how to use them.
· Vision - Papers identifying emerging or future research issues and directions, and describing new research visions related to data-driven innovative solutions and big social data-powered applications to cope with the real-world challenges for building smart cities
Topics of interest include, but are not limited to:
·Data mining of social data for urban planning
·Social data analytics for city evaluation
·Social data integration or fusion
·Social IoT
·Knowledge integration
·Social, Knowledge and Big Data integration
·Urban and city dynamics sensoring
·Crowd dynamics at large scale of events
·Big social data applied to neglected populations
·Traffic and human mobility
·Big social data modeling, visualization, analysis, and prediction
·Urban economics based on social data
·Social behavior modeling, understanding, and patterns mining in urban spaces
·Ethical issues in social data analysis
·Public safety, security, and privacy in urban sensing
·Semantics for big social data
·Visualization of city-wide social data in urban areas
·Smart recommendations in urban spaces
·Mining data from the internet of things in urban areas
·Managing urban big social data in the cloud
·Big social data and IoT frameworks and infrastructures
·Smart city open data
·Ubiquitous/pervasive intelligent social systems in urban areas
·Understanding urban economy based on big social data
·Location-based social networks enabling urban computing scenarios
·Intelligent delivery services in cities
·Influences from the real physical world on social data, and vice versa
IMPORTANT DATES
·May 07, 2018 (Monday): Paper registration to workshop website (23:59 BRT, Brasilia Time, Brazil)
·May 14, 2018 (Monday): Paper submission
·June 18, 2018 (Monday): Communication of workshop presentation decision to authors
·June 25, 2018 (Monday): Final version submission
·Aug 31, 2018 (Friday): Workshop in Rio de Janeiro, Brazil
SUBMISSION INSTRUCTIONS
Research, Experiments and Case Studies, Industry and Application, and Dataset papers submission should be limited to a maximum of 15 pages. Vision papers should be limited to a maximum of 6 pages.
The LNCS format is required (see http://www.springer.com/gp/computer-science/lncs/c...).
All papers will go through a DOUBLE-BLIND REVIEW PROCESS, with at least three reviewers. Therefore, author names and contact information must be omitted from all submissions. Submissions that do not respect this issue will be eliminated from the review process.
All papers will be peer-reviewed according to following criteria: adequacy of workshop scope, relevance, technical quality, clarity, originality, and evaluation of results. The evaluation of results is desired, but is not a precondition for submission. All papers will be presented orally.
The best papers submitted to BiDU will be invited to submit an extended and revised version to an important ISI-impacted journal (to be decided).
Submit your paper using Easy Chair in https://easychair.org/conferences/?conf=bidu20018
PROGRAM CHAIRS
Prof. Jonice Oliveira (Universidade Federal do Rio de Janeiro, Brazil) - jonice-AT-dcc.ufrj.br
Prof. Claudio Miceli (Universidade Federal do Rio de Janeiro, Brazil) - claudiofarias-AT-nce.ufrj.br
Prof. Esther Pacitti (Inria/Cnrs, University of Montpellier, France) - Esther.Pacitti-AT-lirmm.fr
Prof. Giancarlo Fortino (Università della Calabria, Italy) - giancarlo.fortino-AT-unical.it