Linked-data and the Internet of Things

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Linked-data and the Internet of Things
Payam Barnaghi Centre for Communication Systems
Research University of Surrey March 2012
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Future Internet

• Extension
• More nodes, more connections
• Any TIME, Any PLACE, Any THING
• M2M, IoT
• Millions of interconnected devices
• Expansion
• Higher bandwidth
• Spectrum optimisation
• Enhancement
• Smart networks
• Data centric and Content Oriented Networking
• Context-aware networking

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(Future) Web

• Early generation Web focused on Presentation.
• HTML (rendering the pages)
• Dynamic pages (often database to html
  transformation)
• Non-structured
• Semantic Web
• Structured data
• Semantic annotation
• Machine interpretable
• Reasoning and AI enhancements
• Web of Data
• Interconnecting data resources
• Semantic data (i.e. RDF) linked to other data
• Large interconnected data sets

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Future Internet and Future Web

• More Data centric
• Data as
• Content
• Context
• Service oriented developments, Cloud
  infrastructure
• More resources, more nodes, more constraints on
  traffic, energy efficiency, heterogeneity,
• Issues
• Interoperability
• Trust, Privacy and Security
• Resource discovery
• Automated processes
• Autonomous communications

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Current Status

• The current data communications often rely on
  binary or syntactic data models which lack of
  providing machine interpretable meanings to the
  data.
• Binary representation or in some cases XML-based
  data
• Often no general agreement in annotating the data
• Requires an pre-agreement on communication
  parties to be able to process and interpret the
  data
• Limited reasoning based on the content and
  context of the node or communication
• Limited interoperability in data level
• Data integration and fusion issues

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Challenges

• Numbers of devices and different users and
  interactions required.
• Challenge Scalability
• Heterogeneity of enabling devices and platforms
• Challenge Interoperability
• Low power sensors, wireless transceivers,
  communication, and networking for M2M
• Challenge Efficiency in communications
• Huge volumes of data emerging from the physical
  world, M2M and new communications
• Challenge Processing and mining the data,
  Providing secure access and preserving and
  controlling privacy.
• Timeliness of data
• Challenge Freshness of the data and supporting
  temporal requirements in accessing the data
• Ubiquity
• Challenge addressing mobility, ad-hoc access and
  service continuity
• Global access and discovery
• Challenge Naming, Resolution and discovery

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What is expected in service/application level?

• Unified access to data
• unified descriptions and at the same time an open
  frameworks
• Deriving additional knowledge (data mining)
• Reasoning support and association to other
  entities and resources
• Self-descriptive data an re-usable knowledge
• In general Large-scale platforms to support
  discovery and access to the resources, to enable
  autonomous interactions with the resources, to
  provide self-descriptive data and association
  mechanisms to reason the emerging data and to
  integrate it into the existing applications and
  services.

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Using semantically enriched data

• The core technological building blocks are now in
  place and (widely) available ontology languages,
  resource description frameworks, flexible storage
  and querying facilities, reasoning engines, etc.
• There are existing standards such as those
  provided by OGC and W3Cs SSN Ontology.
• However, often there is no direct association to
  the domain knowledge
• What a sensor measures, where it is, etc.
• Association of an observation and/or measurement
  data to a feature of interest.
• We often need to have access to domain
  knowledge and relate semantically enriched
  descriptions to other entities and/or existing
  data (on the Web).

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The role of metadata

• Semantic tagging and machine-interpretable
  descriptions
• Re-usable ontologies (interoperable data and
  knowledge sharing)
• Resource description frameworks
• Semantic models to describe sensors, nodes,
  content, etc.
• Structured data, structured query
• Using metadata and semantic annotation solves
  some of the problems however, interconnected and
  linked metadata is better than stand-alone
  metadata!

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How to create linked-data?

• The principles in designing the linked data are
  defined as
• using URIs as names for things
• Everything is addressed using unique URIs.
• using HTTP URIs to enable people to look up
  those names
• All the URIs are accessible via HTTP
  interfaces.
• provide useful RDF information related to URIs
  that are looked up by machine or people
• The URIs refer to objects that are described
  by machine-interpretable data.
• including RDF statements that link to other URIs
  to enable discovery of other related concepts of
  the Web of Data
• The URIs are linked to other URIs.

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Linked data contributions to M2M and information
communication

• Using URIs as names for things
• URIs for naming M2M resources and data (and also
  streaming data)
• Using HTTP URIs to enable people to look up
  those names
• Web-level access to low level sensor data and
  real world resource descriptions (gateway and
  middleware solutions)
• Providing useful RDF information related to URIs
  that are looked up by machine or people
• publishing semantically enriched resource and
  data descriptions in the form of linked RDF data
• Including RDF statements that link to other URIs
  to enable discovery of other related things of
  the web of data
• linking and associating the real world data to
  the existing data on the Web

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Linked-data to support data interoperability
OSI/OSI Model and envisioned Linked Data
Interoperability Layer
Source Stefan Decker (DERI NUI Galway, Ireland)
, http//fi-ghent.fi-week.eu/files/2010/10/Linked-
Data-scheme1.png
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Linked-data for

• Web data, network, and application data
• (Web) Services and service platforms
• IoT and THING descriptions
• Resource descriptions
• Network resources
• Entities of Interests/Resource/Service
• Content
• Context
• This will enable
• Intelligent decision making
• Network communications
• Information networking

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Linked-data for (contd)

• However, it still is a form of Knowledge and Data
  Engineering
• We still need more intelligent systems, reasoning
  mechanisms, and effective information processing
  and decision making mechanisms to support M2M and
  Future Internet data communications.
• It helps AI methods, but does not replace them

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Payam Barnaghi Centre for Communication Systems
Research Faculty of Engineering and Physical
Sciences University of Surrey Guildford,
UKEmail p.barnaghi_at_surrey.ac.uk
http//personal.ee.surrey.ac.uk/Personal/P.Barnagh
i/payam-foaf.rdf