The linked data value chain atif
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  • Hello every one. I am aatif latif , a phd student at Knowledge management Institute. Technology university of graz. I‘m here, today to present my paper „Linked Open data value chain“. Bascially this publication is inteded to highlight one aspect which is not fully explored in the linked Open data paradigm. That is lack of conceptul ground work for business communities in adaptation of this innovative idea. In this publication we tried to conceptualize whole linked data sphere and to start dicsussion which can bring business community and Semantic web (linked data paradigm) more closer. Before going into further detail of the paper. Let‘s have a look on the agenda of my talk. 07/20/10
  • I am going to start with motivation to highlight what factors motivates us to do this study.Then I will give a brief overview of the work to bring feel about the publication. Further on, basic introduction of the Linked open data project with emphasis on difference of Business and academia interest will be discussed. Further on, Linked data value chain our conceptual model will be discussed in detail. later on case study of BBC wrt linked data vlaue chain along with identified potential risks will be discussed. Further I will conclude my talk by giving conclusion and slight glimpse of ongoing work. In the end I will take your questions and feedback. 07/20/10
  • What was the motivation behind this publication? As most of the audience now have the basic idea of Linked data which has been discussed by already presented talks. I will try to keep it at abstract level. As concluding Linked data project. In the nutsheell, Linked data provides a framework for publishing , interlinking of openly availble dataset. And in span of fours years it attracted interest of many people how publish their diffenrt datasets to make it more interesting. But as the people working in this filed may have noticed there is still a limited adaptaion of Semantic technologies in the commerical/coroporate sector. Why it is so? Along with different aspects (e.g. technichal, complex, user interfaces) which are affecting this process. We envision that a lack of conceptual groundwork which supports the development of business cases and identification of roles is also playing a big role. So motivating by these factors .We proposed a light weight model (A Linked data value chain ) which conceputalizes the whole linked data sphere and we intend to start a discussion which can bring semantic web and business commuitny more closer 07/20/10
  • The sucess of linked data made it a integral part of semantic web. It is considered as important as Hypertext for Web. Bascially Linked open data is facilitating transforamtion of open un-strucutred data to strucutred one by adding more meaning to it. And Most of this data is generated by Research community and institutes. You can only find few examples out side of academia e.g BBC. We invistigated this trend and feel that there is need of strong conceptual frmae work which can help business communites to adapt this technologies. We propsed a light weight model Linked data value chain...... 07/20/10
  • We propose the Linked Data Value Chain as a lightweight model, which builds upon the concepts of Linked Data and Value Chains. This model helps in highlighting the Inter-dependencies of entities, roles and different types of data as the output of the value creation process explicit. And help to identify the potential pitfalls. To check our model we applied this on BBC . 07/20/10
  • I think so we can skip this slide as it is discuessed in previous slides too.I will just talk about the basic vision of linked data. 1. Produce and then consume. 07/20/10
  • Number 1 is to motivate people to publish and interlink data as much possible And then making mashup applications by using this data. At the moment the trend is followed by academia mostly. But there is useful benefits business community can also take is highlighted by servant in his publication. But there are difference in the intereset of the academia/ scientific community and business commuitny. I.e the value generation for their cutomers and revenue flow. To support these assumption there is need of discussion on inherent technichal , social and buisness risks. 07/20/10
  • Adhereing all these shortcomming ( point) . We proposed a coceptual model know as Linked data value chain. This is a light wieght model Which is bulit on the basis of linked data and Value chain.It will help business engineers to identify different kind of roles , data and interactions which can get involvoed in this process. what kind of entite my get involve and interact at diiferent level to prodcue the out put. It help them to analyze phases in more detail and facilating them to indentify risks which may occur in long run and can damage the output along the way. This value chain consits of three tiers basciall. Entities Roles Data interactions 07/20/10
  • Conceptual Framework. Three tiers... Tier 1 Tier 2 Tier 3 07/20/10
  • Value chain was introduced by porter... It is a business concept and in nutshell it talks about the chain of activites producing output, each activity increasing value of the its particlular output and finally produce the most valuable asset Each activity increase the vlaue for the procedding actitivty. Like mention in our Model... Jump to picutre Every proceeding element increase the value along the way giving rise to the high value out put.......... 07/20/10
  • Conceptual Framework. 07/20/10
  • In the context of Linked Data, participating entities -both corporate and non-corporate, e.g. persons, enterprises, associations, and research institutes - can occupy one ore more of the following roles A Raw Data Provider is a role that provides any kind of data in any non- RDF format. A Linked Data Provider is a role that provides any kind of data in a machine- readable Linked Data format. Such data is currently provided through deref- erenceable URIs, a SPARQL endpoint or an RDF dump. A Linked Data Application Provider is a role that processes Linked Data within an application and generates human-readable output for human end users. An End User is a human, consuming a human-readable presentation of Linked Data. He or she does not directly get in touch with Linked Data, and typically does not even want to.: 07/20/10
  • The Linked Data Value Chain allows a exible assignment of roles to entities: In most cases, one entity just occupies one role, but it may in extreme cases also occupy all roles at once. For example, one enterprise could own the role of a Data Provider, a Linked Data Provider, and a Linked Data Application Provider all at the same time. The Linked Data Value Chain also supports multiple sources of data: A Linked Data Provider may acquire Raw Data from more than one Raw Data Provider simultaneously, and will usually provide Linked Data to more than one Linked Data Application Provider. 07/20/10
  • Conceptual Framework. 07/20/10
  • Particulary in Linked data domain three kind of data type occur. Which are Raw data Raw Data is any kind of data (structured or unstructured) that has not yet been converted into Linked Data. Such data usually has some structure, but generally less structure than Linked Data, and is in most cases also not universally identiable. Linked Data Linked Data is data in a RDF format that uses dereferenceable HTTP URIs to identify resources and is linked with other RDF data. This data can be generated by the Linked Data Provider itself, or data provided by a Raw Data Provider can be "RDFized". Linked Data is intended to be consumed and processed by machines only. Human Readable Data Human-Readable Data is any kind of data which is intended, arranged and formatted for consumption by humans. Consuming this data generates value for the human end user, which is crucial to the success of any Linked Data business case. 07/20/10
  • 07/20/10
  • Linked data idea still young so not much appealing interfaces for users and humans One enterprise that is on the cutting edge, both in regard to deployed Semantic Web technologies and the end-user inter- face, is the BBC 07/20/10
  • As I talked about the certian limitations and the pitfalls we identified. We developed a proff of concept appilcation named as CAFSIAL. It is an concept aggregation framework to cluster down the most releavnat Dbpedia property to an aspect in easy to perciveable way. 07/20/10
  • I am also working on an concept aggregation framework. It is a porrf of concept application to cluster out most importnat properties from Dbpedia. Further information about this application can be found at my student website given in bottom of the slide with an email and you can access this online application from cafsial.hoefler.st. Thanks 07/20/10

The linked data value chain atif Presentation Transcript

  • 1. Atif Latif The Linked Data Value Chain: A Lightweight Model for Business Engineers PhD Student (Knowledge Management Institute) Technical University Graz , Austria http://www.student.tugraz.at/atif.latif/ Email: atif.latif@student.tugraz.at
  • 2. Agenda
      • Motivation
      • Overview of Work
      • Linked Open Data
      • Linked Data Value Chain
        • Participating Entities and Linked Data roles
        • Types of Data
        • Interaction between Roles
      • BBC Case Study
      • Discussion and Potential Pitfalls
      • Conclusion
  • 3. Motivation
      • Linked Open Data project provides a framework for publishing and interlinking of data.
      • Limited commercial Semantic Web adaptation
        • Among other reasons (Complex underlying mechanics, quality, trust, user interfaces etc.)
        • Caused by lack of conceptual work supporting the development of business cases and identification of associated risk
      • Motivated by these factors and intended to start discussion which moves business and Semantic Web (Linked Data) closer
  • 4. Overview of Work
      • Linked Data essential for Semantic Web as hypertext for Web
        • Linked Open Data facilitating transformation of openly available unstructured data to structured data
        • Mostly data generated by Research communities and Institutions
      • Few examples of uptake outside of academia (e.g. BBC Music )
      • We deem it is important to have a strong conceptual groundwork.
  • 5. Overview of Work
      • “ Linked Data Value Chain ” as a model that conceptualizes the current Linked Data sphere.
      • Inter-dependencies of entities, roles and different types of data: makes the output of the value creation process explicit
      • Helps in identify and categorize potential pitfalls which have to be considered by business engineers
      • Applied on concrete BBC case study
  • 6. Linked Data
      • Semantic Web has been a great interest to international research community [Berners-Lee, 1998].
      • Linked Data as a sub topic of this concept gained lot of recognition (attention)
      • Based on Tim Berner-Lee Idea [Berners-Lee, 2006]
        • Use URIs as names for things
        • Use HTTP URIs so that people (and machines) can look up those names
        • When someone looks up a URI, provide useful information
        • Include links to other URIs so that they can discover more things
      • Started by SWEO group
      • Motivate people to publish their data in structured Format (RDF)
      • Provide framework for interlinking
  • 7. Linked Data
      • Vision of Linked data scientific community can be described as
        • Facilitate generation of structured ( Linked data)
        • Build applications on top of this data
      • Linked data incorporates lot of potential for enterprise [servant 2008]
      • Significant difference between aims of scientific community and demand, requirements of enterprise i.e. (Revenue flow and value generation)
      • Commercial adaptation requires discussion of inherent technical , social and business risks.
  • 8. What is Linked Data Value Chain
      • A light weight model which is build upon concept of Linked Data and Value Chain
      • Making interdependencies, role assignment and data transformation more explicit
      • Linked Data Value chain consists of three components
  • 9. The Linked Data Value Chain
  • 10. What is a Value Chain?
      • The value chain was introduced by [Porter 1985]
      • In a nutshell,
      • “ A value chain is a chain of activities producing outputs, each activity increasing the value of its particular output, finally shaping a highly valuable end product”
      • In the case of Linked Data with respect to business cases, Human-Readable Data is the most valuable output for the targeted End User.
  • 11. The Linked Data Value Chain (our contribution)
      • Three types of concepts
      • Participating entities
      • Linked data roles
      • Types of data
      • Contribution tries to support Business engineers in
      • Assigning linked data roles to Entities
      • Modeling interaction ( activities ) and responsibilities of Linked Data roles
      • Showing how to transform Raw data to linked data and finally to Human readable data
  • 12. The Linked Data Value Chain
  • 13. Linked Data Roles
      • Raw Data Provider:
        • Any kind of data in non RDF format
      • Linked Data Provider:
        • Data in machine readable format e.g de-referencable URI , SPARQL endpoint
      • Linked Data Application Provider:
        • Processed Linked data and generate human readable data
      • End User:
        • Consuming human readable presentation of Linked data
  • 14. Pariticpating Entites
      • Corporate or non corporate entities
      • Persons, Associations and Research institutes etc.
  • 15. Assigning Roles to Entities
      • Linked Data Value Chain allows flexible assignment of roles
      • In most cases , one entity just occupy one role.
      • But in extreme cases, one entity can have more than one or all role at one time
      • Also different one role can interact with more than one particular role instances.
  • 16. The Linked Data Value Chain
  • 17. Types of Data
      • Raw Data
        • Any kind of structured/unstructured data that has not been converted to Linked data
      • Linked Data
        • RDF format that uses de-referencable HTTP URI‘s and linked with other resources
      • Human-readable Data
        • Data which is intended, arranged formatted for human consumption
  • 18. Interaction between Roles and Data
      • Roles are closely connected through three types of data (provide, produce or consume)
      • Raw Data provider provides raw data as input for Linked data provider , turns it into Linked Data increasing its value by semantically enriching it. Linked data serves as basis for Linked data application provider who generates Human readable data as most valuable output
  • 19. Identified Pitfall Areas
      • Each combination of roles and entities as well as every transformation step of data holds inherent risks.
      • We identified two areas where pitfall may arise
      • Role-Related Pitfalls
        • Role-Related Pit-falls are either related to individual roles or to the interaction of different roles.
      • Data-Related Pitfalls
        • Data-Related Pitfalls are either related to the data itself or the data transformation process
  • 20. Case Study : BBC
      • One Enterprise on cutting edge , deployed Semantic technologies and interfaces is BBC
      • Pioneer when it comes to adopting Linked Data within a business case
      • Their system utilizes Linked Data technologies to interconnect distributed micro-sites within the BBC network e.g. news, food, music etc
      • Utilizing external resources like DBpedia, MusicBrainz for addition to end user value
  • 21. Linked Data Roles and Participating Entities in BBC case study
  • 22. Potential Pitfalls
      • Tansforming data is time consuming and semi-automatic effort (completeness, correctness, up-to-dateness )
      • No automated feed back loop leading back to raw and Linked Data provider
      • Long transformation intervals
      • Links to third party site might take traffic away (Widget)
  • 23. Conclusion
      • Dedicated to facilitate the commercial uptake of the Semantic Web vision
      • Linked Data Value Chain as a lightweight model for business engineers to support the conceptualization of successful business cases.
      • We identified three main concepts: Different Entities acting in different Roles, both consuming and providing different Types of Data.
  • 24. Ongoing Work
      • Certain Limitations and Pitfalls identified
      • We built a proof of concept application
      • Bridge a gap between Semantic Search and end users.
      • A simplified keyword search mechanism which hides the complex underlying semantic search logic
      • A novel Concept Aggregation Framework to present the most relevant information of LOD resources in an easy to understand way.
      • Online Access at http://cafsial.opendatahub.org/
      • Publication at http://www.student.tugraz.at/atif.latif/
  • 25.  
  • 26. Thanks! Questions? http://www.student.tugraz.at/atif.latif/ Email: atif.latif@student.tugraz.at