
WWW2012 – Web of Things Tutorial
TITLE
The Web of Things
PRESENTERS
Carolina Fortuna
Address: J. Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia
E-mail: carolina.fortuna@ijs.si
Web: https://carolinafortuna.com/
Phone: +386 1 477 3114
Carolina Fortuna’s research interests are interdisciplinary focusing on semantic technologies with applications in modeling of communication and sensor systems, and on combining semantic technologies, statistical learning and networks for analyzing large datasets. She works at the Department of Communication Systems at the “Jozef Stefan Institute”, Ljubljana, Slovenia since 1996. She is one of the leaders of the SensorLab group which consists of approximately 10 PhD students. She has actively participated in FP6 and FP7 projects and gained industry experience by interning with Bloomberg LP and Siemens PSE.
Marko Grobelnik
Address: J. Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia
E-mail: marko.grobelnik@ijs.si
Web: http://ailab.ijs.si/marko_grobelnik/
Phone: +386 1 477 3778
Marko Grobelnik is an expert in the areas of analysis of large amounts of complex data with the purpose to extract useful knowledge. In particular, the areas of expertise comprise: Machine Learning, Data/Text Mining, Link Analysis, Semantic Technologies, and Data Visualization. Marko works at “Jozef Stefan Institute”, the national research institute for natural sciences in Slovenia where he manages research group of approx. 30 researchers. He collaborates with major European academic institutions and industries such as Bloomberg, British Telecom, European Commission, Microsoft Research, New York Times. Marko is also co-author of several books, co-founder of four start-ups and is/was involved into over 25 EU projects.
DURATION
Half day (3 hours). The tutorial will address the vertical of the Web of Things, explaining all components from bottom up (i.e. things with focus on sensors, interconnection of the things) with focus on the Web integration. The tutorial could be scaled to 6 hours by providing several hands-on examples of integration if necessary.
The aim of this tutorial is to present the Web of Things (WoT), its components and how they integrate into the World Wide Web. The goal is (1) to explain WoT and related concepts, (2) to give an overview and explain the functionality of the components of the WoT, (3) explain how these components (sensor networks, semantic web, machine learning and data mining) can be used to connect the “things” various levels of abstraction and (4) show relevant projects and demos.
TOPIC AND DESCRIPTION
The tutorial on Web of Things will discuss the vertical of the system by identifying the relevant components, illustrating their functionality and showing existing tools and systems. First the tutorial will cover architectural aspects and discuss the levels of abstraction for integrating the “things” into the web. Then, the tutorial will focus on semantic technology and analytic methods for leveraging services and applications on top of the things. Finally, through live demos, state of the art technology and tools will be showed. Existing projects and research directions will also be provided.
Part I. Motivation & background
- Web Of Things
- …what is WoT?
- … why do we need WoT?
- …what problems can it solve?
- Architectural considerations
- showing possible verticals from hardware to software
- identify important components: “things”, the “glue”, the applications and services
- The “Things”
- …sensors and sensor networks
- …fixed versus mobile sensors
- …beyond common sensors
- The “Glue”
- …the network
- …the communication channel: wired, wireless
- …middleware: operating system, virtual machine, distributed/centralized storage and retrieval
- Data and meta-data
- Applications and services
- General purpose distributed sensor platforms
- Sensor as a service
- Quick start recipes
- how to start working in the area
- steps to build a vertical
Part II. Technology and tools for exploiting the WoT
- Semantic aspects
- how to organize sensor data
- how to describe sensor setups (mark-up languages, ontologies, etc.)
- how to describe sensor data (ontologies, enrichment, contextualization)
- Analytic aspects
- machine learning approaches to deal with sensor data
- introduction into stream mining
- introduction into complex event identification
- Services on the top of sensor setups
- categorization of services
- formalization of services and connection to standardization
- examples of simple services
Part III. Demos, Tools & Research directions
- Applications and ongoing projects
- Small-size setups: e.g. ambient intelligence
- Mid-size setups: e.g. some indoor setups / agriculture monitoring
- Large scale setups: e.g. smart cities & smart grids
- Live demos of existing systems (can be turned into hands-on)
- Manual and automatic annotation of sensors and their data
- Services on top of sensor data-stream
- Open problems, future developments
- Literature, list of sources for further studies
Summary
AUDIENCE
This tutorial is designed for an audience interested in technology and tools for building the Web of Things. Professional profiles expected to be interested in the topic are:
- Researchers and practitioners who are unfamiliar with the topics but wish to learn and understand more about the Web Of Things, Physical Web, Internet of Things, Sensor as a Service and large sensor based smart systems
- Researchers and practitioners who are experts in a subset of the components of the WoT vertical and wish to broaden their knowledge, learn how connect the components, or find inspiration
- Researchers and practitioners who wish to implement the vertical
- General audience interested in possibilities offered by sensors, state of the art knowledge management and analytic tools.
PREREQUISITE
Basic technical education is assumed. Prerequisite knowledge in any of the areas of the vertical is not necessary as all the components will be explained, their functionality within the vertical will be illustrated through explanations, analogies and demos.
RELEVANCE
The tutorial is relevant for WWW2012 particularly because it shows how small devices can be connected to the web on various levels of abstraction and transform them into “first-class residents” of the web. The WoT vertical is relevant for an extensive range of application areas from ambient intelligence, agriculture and wildlife monitoring, logistics, smart cities, energy grids, etc. The tutorial is timely as global challenges such as overpopulation, intense urbanization in developing regions and climate change push for smart, large scale monitoring and optimizations.
PREVIOUS VERSIONS
There were three versions of this tutorial:
- WWW2011 – World Wide Web Conference 2011: The Web of Things.
- Slides: http://sensorlab.ijs.si/files/publications/2011-June-29-Fortuna-Grobelnik-Web-of-Things-Tutorial-ESWC.pdf
- Abstract: http://sensorlab.ijs.si/files/publications/Fortuna_Grobelnik_Web_Of_Things_Abstract_WWW2011.pdf
- Videolecture: http://videolectures.net/www2011_grobelnik_fortuna_wot/
- 30 participants.
- ESWC2011 – European Semantic Web Conference 2011 – The Web of Things.
- ACTIVE-COIN Summer School 2010.
- Videolecture: http://videolectures.net/coinactivess2010_fortuna_dfs/
- 20 participants.
If accepted, the WWW2012 tutorial on WoT will update the existing version with new technology and demos.
PAST EXPERIENCE
Marko Grobelnik has extensive experience also in organizing of workshops on text mining and link analysis at major machine learning, data mining and AI world events:
- ECML/PKDD 2001 – “Text Mining: What if your data is made of words?” (http://www.afia.polytechnique.fr/CAFE/ECML01/text_mining.html).
- WWW 2004 – Tutorial on Text Mining approaches for Web Data (http://www2004.org/tutorial.htm)
- ESWS 2004 – Tutorial on Knowledge Discovery & the Semantic Web (http://www.esws2004.org/sub/tutorials.htm)
- ISWC 2006 – Tutorial on “Context Sensitivity” in Knowledge Rich Systems (http://iswc2006.semanticweb.org/workshop_tutorial/tutorials.php)
- KDD 2007 – Text Mining and Link Analysis for Web and Semantic Web (http://www.kdd2007.com/tutorials.html)
- IJCAI 2009 – Text Mining and Link Analysis for Web and Semantic Web (http://ijcai-09.org/tutorials/tutorial-SP4.html)