Title: Linked-data and the Internet of Things
1Linked-data and the Internet of Things
Payam Barnaghi Centre for Communication Systems
Research University of Surrey March 2012
2Future 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
3(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
4Future 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
-
5Current 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
6Challenges
- 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
6
7What 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.
8Using 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).
9The 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!
10How 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.
11Linked 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
12Linked-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
13Linked-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
14Linked-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
15Payam 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