Description
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 preeminent
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 and analyzing
them for intelligent patterns. This effort needs access to city data,
semantic models to abstract city domains as well as interconnect them so
that advanced applications can be built by rest of the world. We will like
to call cities that enable such capabilities as, “semantic cities”.
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.
Two major trends are supporting semantic cities – open data and semantic
web. “Open data is the idea that data should be accessible from
everyone to use and republish as they wish, without restrictions from
copyright, patents or other mechanisms of control1.” A number of cities and
government have made their data publicly available, prominent being London
(UK), Chicago (USA), Washington DC (USA), Dublin (Ireland). Semantic web as
the technology to inter-connect heterogeneous data has matured and it is
being increasing used in the form of Linked Open Data and formal
ontologies. Thus, a playfield for more AI research-driven technologies for
cities has emerged e.g., scalable, efficient, robust, optimal AI techniques.
In this context, the aims of the workshop are to:
1. Draw the attention of the AI community to the research challenges and
opportunities in semantic cities.
2. Draw the attention on the multi-disciplinary dimension and its impact on
semantic cities e.g., transportation, energy, water management
3. Identify unique issues of this domain and what new techniques may be
needed. As example, since governments and citizens are involved, data
security and privacy are first-class concerns.
4. Promoting more cities to become semantic cities
5. Elaborating a (semantic data) benchmark for testing AI techniques on
semantic cities
6. Provide a platform for sharing best-practices and discussion
We encourage submissions that show the relevance or application of AI
technologies for computational sustainability domains. In addition to a focus on
foundational technologies for semantic cities (information management,
knowledge management, ontology, inference model, data integration), we want
to promote illustrative use-cases using the semantic cities foundation.
Examples are transportation (traffic prediction, 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 also encourage submissions that address unique
characteristics of standard AI enabling sustainability problems, like
optimization, reasoning, planning and learning. Outside AI, we encourage
submission from communities engaged in open data and corresponding
standardization efforts, to make their work available at this AI forum.
Topics of interest include, but not restricted to, are:
1. Process to open city (government) data
2. Platforms to manage government data
3. Provenance, access control and privacy-preserving issues in open data
4. Data cities interoperability
5. Semantic models – especially those built collaboratively and evolving
6. Data integration and organization in semantic cities (social media
feeds, sensor data)
7. Internet of Things in semantic cities
8. Robust inference models for semantic cities
9. Semantic Event detection and classification
10. Applications in semantic cities
11. Spatio-temporal analysis and visualization
12. User interaction in exploring semantic data of cities
13. Knowledge representation and reasoning challenges
14. Knowledge acquisition, evolution and maintenance
15. Challenges with managing and integrating real-time and historical data
16. Managing “big data”
17. Integrated systems
18. Applied AI models for semantic cities
19. Issues in scaling out AI techniques for semantic cities
20. Case Studies, successes, lessons learnt
21. Public datasets and competitions
Workshop Plan
Workshop Format: The workshop will consist of papers and poster
presentations, a panel, an invited talk, and discussion sessions, in a one
full day schedule. The invited talk will invite a leading expert in the
field to present their research and vision of future work. The panel will
focus on connecting the AI researchers to the various challenges that the
targeted domain brings.
Submission Guidelines:All papers submissions must be in AAAI format.
They can be one of two types. The first is regular research papers which
can be up to 6 pages long and are expected to present a significant
contribution. The second is short submission of up to 4 pages which
describes a position on the topic of the workshop or a demonstration/tool.
Submission site: Papers are to be submitted online at at http://www.easychair.org/conferences/?conf=semanticcitiesaaai20. We request interested authors to login and submit abstracts as an expression of interest before the actual deadline.
The Organizers
Co-Chairs:
Biplav Srivastava
IBM T.J.
Watson Research
Center, Hawthorne, USA
Email: sbiplav at in.ibm.com
Freddy Lecue
IBM Research – Smarter Cities Technology Centre, Dublin, Ireland
Email : freddy lecue at ie.ibm.com
Anupam Joshi
University of Maryland, College Park, USA
Email: joshi at cs.umbc.edu
Steering Committee:
Pol Mac Aonghusa, IBM
SCTC – Dublin
Craig Knoblock , Information Sciences Institute, University of Southern California, USA
Rahguram Krishnapuram,
IBM Research - India
Program Committee:
Mathieu D’Aquin, Open University, UK
Pol Mac Aonghusa, IBM Research, Smarter Cities Technology Centre, Dublin, Ireland
Soren Auer, Univeristy of Leipzig, Germany
Philippe Cudré-Mauroux, University of Fribourg, Switzerland
Michael Hausenblas, DERI, Galway, Ireland
Anupam Joshi, University of Maryland, College Park, USA
Subbarao Kambhampati, Arizona State University, USA
Spyros Kotoulas, IBM Research, Smarter Cities Technology Centre, Dublin, Ireland
Craig Knoblock, USC/ISI and Fetch Technologies, USA
Raghuram Krishanpuram, IBM Research, India
Freddy Lecue, IBM Research, Smarter Cities Technology Centre, Dublin, Ireland
Ullas Nambiar, IBM Research, India
Ulrike Sattler, The University of Manchester, UK
Francois Scharffe, LIRMM, Montpellier, France
Biplav Srivastava, IBM Research India, New Delhi, India
Rosario Usceda-Sosa, IBM T.J. Watson Research Center, USA
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