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Related Work Across Scenarios

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PLEASE DO NOT EDIT THIS PAGE: Instead, edit the individual scenario pages.

Related Work in the Three Flagship Scenarios

This section contains a summary of the related work cited in the original use cases that were used to create the three flagship scenarios.

News Aggregator

  1. Use_Case_Retweets
    1. An excellent discussion of the issues with retweeting and the introduction of retweet functionality can be read in a blog post by Evan Williams: Why Retweet works the way it does
  2. Use_Case_Provenance_in_Blogosphere
    1. The SIOC project has developed a vocabulary for representing posts. This vocabulary is often used together with FOAF (that represent information about the physical person related to a sioc:User, e.g. its name, lastname, phone, social network, etc.) and SKOS, used mainly to represent topics and taxonomy relationships between these topics.
  3. Use_Case_Creative_Commons
    1. http://wiki.creativecommons.org/Reuse_Tracking
    2. LibLicense
    3. Google Books rights registry
  4. Use_Case_Mapping_Digital_Rights
    1. The Open Digital Rights Language (ODRL): http://odrl.net/
    2. Creative Commons (CC): http://creativecommons.org/
    3. Digital Rights Management (DRM): http://en.wikipedia.org/wiki/Digital_rights_management
    4. liblicense: http://wiki.creativecommons.org/Liblicense
  5. Use_Case_Attribution_for_a_Versioned_Document
    1. None indicated
  6. Use_Case_Identifying_Attribution_And_Associations
    1. [Gil and Ratnakar ISWC02] describe an approach to enable users to express their assessment of complementary and contradictory sources of information. As the user considers information from different sources relevant to their purpose, they can view the ratings that other users assigned to the entities involved, and use those ratings to assess the information at hand. Sources were assigned a reliability rating, and individual sources could be selected to express the criteria used to accept or dismiss information. The user could also assign credibility ratings based on other information available.

Disease Outbreak

  1. From Use_Case_Evidence_for_Public_Policy
    1. Use case drawn from work reported by Peter Edwards and Lorna Philip, University of Aberdeen. (See http://wiki.esi.ac.uk/UseCasesForProvenanceWorkshop).
  2. From Use_Case_Provenance_of_Decision_Making_Emergency_Response
    1. None indicated
  3. From Use_Case_Provenance_for_IQ
    1. D. Stead, N. Paton, P. Missier, S. Embury, C. Hedeler, B. Jin, A. Brown, and A. Preece, "Information Quality in Proteomics," Briefings in Bioinformatics, vol. 9, 2008, pp. 174-188.
    2. P. Missier, S.M. Embury, R.M. Greenwood, A.D. Preece, and B. Jin, "Managing information quality in e-science: the Qurator workbench," SIGMOD '07: Proceedings of the 2007 ACM SIGMOD international conference on Management of data, New York, NY, USA: ACM, 2007, pp. 1150-1152.
  4. From Domain_Specific_Provenance_2
    1. Semantic Provenance for eScience: ‘Meaningful’ Metadata to Manage the Deluge of Scientific Data
    2. Ontology-driven Provenance Management in eScience: an Application in Parasite Research
  5. From Use_Case_Result_Differences
    1. An approach to addressing this use case is discussed in the paper Recording and Using Provenance in a Protein Compressibility Experiment
  6. From Closure_of_Experimental_Metadata
    1. None indicated
  7. From Use_Case_private_data_use
    1. Aldeco-Pérez, R. & Moreau, L. Provenance-based Auditing of Private Data Use International Academic Research Conference, Visions of Computer Science, 2008 [1]

Business Contract

  1. Use_Case_Fulfilling_Contractual_Obligations
    1. There is work across electronic records, e-notbooks, LIMS and asset management systems, workflow, e-Science, and semantic web commuities that address parts of this scenario. I've drawn from experience as part of the Collaborative Electronic Notebook Systems Association (censa.org, 1998-2008) where many requirements for documentation of scientific research and analyical sample processing in the Chemical and Pharmaceutical industries were discussed in the context of FDA regulatons, patent policies, and rules of legal evidence.
  2. Use_Case_Evidence_for_Engineering_Design
    1. This is (very loosely) based on discussion of provenance in engineering design by Alex Ball (see http://wiki.esi.ac.uk/UseCasesForProvenanceWorkshop).
    2. Toyota Recall
  3. Use_Case_Hidden_Bug
    1. None indicated
  4. Use_Case_Crosswalk_Maintenance
    1. Working examples by means of RDF Reification can be found here: DC-09 conference article
  5. Use_Case_Metadata_Merging
    1. Working examples by means of RDF Reification can be found here: DC-09 conference article
  6. Use_Case_Linked_Data_Timeliness
    1. [Hartig and Zhao SWPM09] describe an approach to develop a timeliness assessment method for Web data.

Related Work Compiled by the Group that Needs to be Incorporated into the Related Work Section of the Scenarios

Related Work from Other Use Cases

  1. Anonymous Information
    1. None indicated
  2. Information Quality Assessment for Linked Data
    1. Felix Naumann: Quality-Driven Query Answering for Integrated Information Systems. Springer Berlin / Heidelberg, 2002.
    2. Christian Bizer: Quality-Driven Information Filtering in the Context of Web-Based Information Systems. Thesis, Freie Universität Berlin, 2007.
    3. Tim Berners-Lee: Cleaning Up the User Interface, Section: The "Oh,yeah?"-Button, 1997.
    4. Olaf Hartig: Querying Trust in RDF Data with tSPARQL. In Proceedings of the 6th European Semantic Web Conference (ESWC), Heraklion, Greece, June 2009
    5. Olaf Hartig: Provenance Information in the Web of Data. In Proceedings of the Linked Data on the Web (LDOW) Workshop at WWW, Madrid, Spain, April 2009 Download PDF
  3. Simple Trustworthiness Assessment
    1. Hartig ESWC09 describes tSPARQL which is a trust-aware extension to the query language SPARQL. tSPARQL allows to describe trust requirements in SPARQL queries. Using tSPARQL an application can filter (intermediate) solutions for graph patterns in SPARQL queries based on the trustworthiness of the data from which the solutions originate. The tRDF4Jena library provides a query engine for tSPARQL.
  4. Ignoring Unreliable Data
    1. See WIQA framework on IQ in Linked Data main page.
  5. Answering user queries that require semantically annotated provenance
    1. We are aware of an early prototype where domain-specific provenance is added to OPM, and such semantics-augmented OPM is represented using RDF. This is described in a paper presented at the SWPM'09 workshop (ISWC'09): SWPM'09 paper
    2. Semantic extensions to OPM have also been recently proposed in this paper, presented at the 2009 All Hands Meeting, Oxford, UK.
    3. Additionally, [KDG+08] describes reasoning about semantic properties of datasets in the workflow as part of provenance records. [GGR+09] describes how this is done for the case of data collections.
  6. Using process provenance for assessing the quality of Information products
    1. D. Stead, N. Paton, P. Missier, S. Embury, C. Hedeler, B. Jin, A. Brown, and A. Preece, "Information Quality in Proteomics," Briefings in Bioinformatics, vol. 9, 2008, pp. 174-188.
    2. P. Missier, S.M. Embury, R.M. Greenwood, A.D. Preece, and B. Jin, "Managing information quality in e-science: the Qurator workbench," SIGMOD '07: Proceedings of the 2007 ACM SIGMOD international conference on Management of data, New York, NY, USA: ACM, 2007, pp. 1150-1152.
  7. Provenance of Collections vs Objects in Cultural Heritage
    1. None indicated
  8. Provenance at different levels in Cultural Heritage
    1. None indicated
  9. Documenting axiom formulation
    1. The use case is described in terms of the use of semantic web ontologies and data, but its motivation comes from uses of ontologies for engineering problems. Consider for example a system developed to estimate the duration of carrying out specific engineering tasks, such as repairing a damaged road or leveling uneven terrain. Users invariably wanted explanations about where the answers came from in terms of the sources we consulted and the sources that we chose to pursue. They wanted to know whether well-known engineering manuals were consulted, which were given more weight, whether practical experience was considered to refine theoretical estimates, and what authoritative sources were consulted to decide among competing recommendations. In other words, the analysis process that knowledge engineers/developers perform is part of the rationale that needs to be captured in order to justify answers to user queries.
    2. [Gil EKAW 02] describes a tool that enables knowledge base developers to keep track of the knowledge sources and intermediate knowledge fragments that result in a formalized piece of knowledge. The resulting ontology is enhanced with pointers that capture the rationale of its design and development.
  10. Provenance for Environmental Marine Data
    1. J. Carroll, C. Bizer, P. Hayes, and P. Stickler. Named graphs, Provenance and Trust. In WWW, 2005.
    2. P. Pediaditis, G. Flouris, I. Fundulaki, and V. Christophides. On Explicit Provenance Management in RDF/S Graphs. In TAPP, 2009.
    3. G. Flouris, I. Fundulaki, P. Pediaditis, Y. Theoharis, and V. Christophides. Coloring RDF Triples to Capture Provenance. In ISWC, 2009.
    4. PSPARQL. psparql.inrialpes.fr.
    5. J. Perez, M. Arenas, and C. Gutierrez. nSPARQL: A Navigational Language for RDF. In ISWC, 2008.
    6. P. Buneman, J. Cheney, and S. Vansummeren. On the Expressiveness of Implicit Provenance in Query and Update Languages. In ICDT, 2007.
    7. T. J. Green, G. Karvounarakis, and V. Tannen. Provenance semirings. In PODS, 2007.
    8. Simon Schenk Steffen Staab. Networked Graphs: A Declarative Mechanism for SPARQL Rules, SPARQL Views and RDF Data Integration on the Web. In WWW 2008.
  11. Computer Assisted Research
    1. None indicated
  12. Handling Scientific Measurement Anomaly
    1. None indicated
  13. Human-Executed Processes
    1. None indicated
  14. Semantic disambiguation of data provider identity
    1. P. Bouquet, T. Palpanas, H. Stoermer, and M. Vignolo, "A Conceptual Model for a Web-scale Entity Name System," in ASWC, Shanghai, China, 2009
    2. http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData
    3. A. Jaffri, H. Glaser, and I. Millard. Uri identity management for semantic web data integration and linkage. In 3rd International Workshop On Scalable Semantic Web Knowledge Base Systems. Springer, 2007
    4. P. Bouquet, H. Stoermer “OKKAM : Enabling an Entity Name System for the Semantic Web” in: Proceedings of the I-ESA2008 Workshop on Semantic Interoperability, 2008

Related Work from State-Of-The-Art Presentations

Other topics discussed by the group:

  • Security and digital signatures
  • Social Web
  • e-Government
  • Policies, trust, and privacy

Relevant Technologies and Standards for the Working Group

Survey Papers

Online Paper Collections

  • Mendeley Collection. This bibliography is publicly readable. If you would like to have write access, send email to Paolo Missier.