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The IJCAI 2015 Workshop on Semantic Cities: Beyond AI Models, Proofs and Reasoning |
IMPORTANT CANCELLATION NOTICE: The workshop has been cancelled due the limited number of submissions.
Cities around the world aspire to provide superior quality of life to their citizens. Furthermore, many are also seen as centers of unique opportunities, like business, fashion, entertainment and governance, for their citizens. Cities want to retain such pre-eminent positions or re-position themselves for newer opportunities. But, resources needed to reach and sustain such aspirations are decreasing while the expectations continue to rise from an increasing population-base. A positive trend of the Internet age is that more data than even before is open and accessible, including from governments at all levels of jurisdiction, which enables rigorous analysis.
The scientific community has responded to city challenges by promoting the computational sustainability vision where resources consumed by a city, such as water, energy, land, food and air, can be monitored to know the accurate present picture and then optimized for resource efficiency without degrading quality of services it provides -traffic movement, water availability, sanitation, public safety, etc. Industry has joined the vision with a "smart" or "intelligent" prefix for cyber-physical systems, which involve sensing the data through physical instruments, interconnecting and integrating them from multiple sources, analyzing them for intelligent patterns and inferring new insight for decision making. This effort needs access to city data, AI models to abstract city domains as well as interconnect them so that advanced AI techniques, AI reasoning and new generation of applications can be built by rest of the world. We will like to call cities that enable such capabilities as, "semantic cities". In particular this workshop addresses "Beyond AI models, proofs and reasoning" where models and reasoning techniques from the AI community are of special interest.
In a Semantic City, available resources are harnessed safely, sustainably and efficiently to achieve positive, measurable economic and societal outcomes. Enabling City information as a utility, through a robust (expressive, dynamic, scalable) and (critically) a sustainable technology and socially synergistic ecosystem could drive significant benefits and opportunities. Data (and then information and knowledge) from people, systems and things is the single most scalable resource available to City stakeholders to reach the objective of semantic cities.
A number of cities and government have made their data publicly available, prominent being New York (USA), London (UK), Chicago (USA), Washington DC (USA), Dublin (Ireland) and Rio de Janeiro (BR). The New York City can be considered one of the leaders in this area.
Two major trends are supporting semantic cities - open data and Artificial Intelligence. "Open data is the idea that certain data should be freely available to everyone to use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control ." Artificial Intelligence as a mature research discipline is crucial to bring breakthrough new technologies and systems to cities, its operators and citizens. Thus, a playfield for more AI research-driven technologies for cities has emerged.
In this context, the aims of the workshop are to:
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Draw the attention of the AI community to the research challenges and opportunities in semantic cities.
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Draw the attention on the multi-disciplinary dimension and its impact on semantic cities e.g., transportation, energy, water management, building, infrastructure
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Identify unique issues of this domain and what new (hybrid) techniques may be needed. As example, since governments and citizens are involved, data security and privacy are first-class concerns.
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Promoting more cities to become semantic cities.
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Elaborating a (semantic data) benchmark for testing AI techniques on semantic cities.
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Provide a platform for sharing best-practices and discussion.
We will encourage submissions that show the relevance or application of AI technologies for computational sustainability domains. Apart from focus on foundational technologies for semantic cities (information management, knowledge management, ontology, inference model, data integration, machine learning, crowdsourcing), we will promote illustrative use-cases using the semantic cities foundation. Examples are transportation (traffic prediction, diagnosis, personal travel optimization, carpool and fleet scheduling), public safety (suspicious activity detection, disaster management), healthcare (disease diagnosis and prognosis, pandemic management), water management (flood prevision, quality monitoring, fault diagnosis), food (food traceability, carbon-footprint tracking), energy (smart grid, carbon-footprint tracking, electricity consumption forecasting) and buildings (energy conservation, fault detections). We will also encourage submissions that address unique characteristics of standard AI enabling sustainability problems, like optimization, reasoning, planning and learning. We will also "reach out" to communities engaged in open data and corresponding standardization efforts.
Topics of interest include, but not restricted to, are:
- AI models and analytics for cities
- Active learning, sampling biases and dataset shift in city data
- Process to open city (government) data
- Platforms to manage government data
- Planning/Scheduling for city operations
- Provenance, access control and privacy-preserving issues in open data
- Data cities interoperability
- Decision making for urban science and for city policy
- Resource allocation in urban systems
- Crowdsourcing for urban science and decision making
- Semantic models - especially those built collaboratively and evolving
- Data integration and organization in semantic cities (social media feeds, sensor data)
- Internet of Things in semantic cities
- Robust inference models for semantic cities
- Semantic Event detection and classification
- Applications in semantic cities
- Spatio-temporal reasoning, analysis and visualization
- User interaction in exploring semantic data of cities
- Knowledge representation and reasoning challenges
- Knowledge acquisition, evolution and maintenance
- Challenges with managing and integrating real-time and historical data
- Managing "big data" using knowledge representation models
- Multi-agent simulations of urban processes
- Integrated systems
- Applied AI models for semantic cities
- Issues in scaling out and applying AI techniques for semantic cities
- Case studies, successes, lessons learnt
- Public datasets and competitions
- Intelligent user interface
The Center for Urban Science and Progress (CUSP) is a unique public-private research center that uses New York City as its laboratory and classroom to help cities around the world become more productive, livable, equitable, and resilient. CUSP observes, analyzes, and models cities to optimize outcomes, prototype new solutions, formalize new tools and processes, and develop new expertise/experts. These activities will make CUSP the world’s leading authority in the emerging field of "Urban Informatics."