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LODFlow
Workflow Management System for Linked
Data Processing
Sandro Rautenberg, Ivan Ermilov,
Edgard Marx, S?ren Auer, and Axel-Cyrille N. Ngomo
Agenda
● Introduction
● Linked Data Workflow Management
● LODFlow: LD Workflow Management
System
● LODFlow: Use Cases
● Related Work
● Conclusion and Future Work
Intro: A Bird’s Eye View on The Problem
Creation and
Maintenance of
LD Datasets
manual
workflows
applying
scripts
cumbersome
time-
consuming
error-
prone
requiring
skills
Linked Data
Workflow
Management
supported by a
systematic way
be component-
oriented
enabling the reuse
of process
facilitating the resource
provenance and reproducibility
ensuring the
correctness
supporting the
evolution
Intro: Solution Outline
Linked Data
Workflow Documentation
Linked Data
Workflow Repeatability
Linked Data Workflow Management
System
Requirements
Linked Data
Workflow Planning
Linked Data
Workflow Execution
Linked Data
Workflow Reusability
LODFlow
Benefits:
● Explicitness
● Reusability
● Repeatability
● Efficiency
● Ease to use
LODFlow: LDWPO ontology (abstract)
The Linked Data Workflow
Knowledge Model and
Knowledge Base
LODFlow: Architecture
Qualis: LODFlow Use Case
indirect scores for
periodical papers,
according 48
knowledge fields.
http://qualis.capes.gov.br/webqualis/publico/pesquisaPublicaClassificacao.seam?conversationPropagation=begin
use in bibliometric
and scientometric
studies and for
ranking post-
graduate programs,
research proposals,
or individual
research
scholarships.
Qualis (cont.)
● Problem:
○ Data available only as 1 Star Data
○ Only the current version is available
○ Data is not linked to other datasets
● Solution:
○ Extracted the data from the web interface (10 years)
○ Converted Qualis to a 5-star dataset
○ Interlinked it to the DBpedia knowledge base
Qualis: Workflow
● Create a plan for LD project
○ Planning the maintenance of LD datasets
○ Managing the lifecycle of resources
● Execute a plan
○ Maintaining the provenance and repeatability
information
○ Producing the resources
Qualis: Workflow (cont.)
Qualis: Workflow Implementation
Create
a plan for
LDProject
Workflow Implementation (cont.)
Execute
a plan
Qualis: Results
● Were executed over 10 years
● LODFlow fulfills the requirements
Related work
● Languages such as Business Process
Execution Language are adopted in
technologies
● Scientific Workflow Management Systems,
such as Apache Taverna and Kepler were
developed
Conclusion
● Automatization of processing LD workflows
● Preserving provenance information on (re)
producing LD datasets
● Showing the benefits of explicitness,
reusability, repeatability and efficiency
● Applicable in the context of the LODStack
and LD Lifecycle.
Future work: Integration with LODStack
Developing a
tool to integrate
LODFlow to the
LODStack.
Improving the
LDWPO with
Method
concepts
Future work: New Use Cases
research group extracted
from a transparency portal
Qualis
classification set of papers extracted
from Lattes CV
Thank you for your attention!
srautenberg@unicentro.br
sandro.rautenberg@gmail.com
We acknowledge support from CAPES/Brazil
Agency as well as BMWi SAKE project.

More Related Content

LODFlow: Workflow Management System for Linked Data Processing

  • 1. LODFlow Workflow Management System for Linked Data Processing Sandro Rautenberg, Ivan Ermilov, Edgard Marx, S?ren Auer, and Axel-Cyrille N. Ngomo
  • 2. Agenda ● Introduction ● Linked Data Workflow Management ● LODFlow: LD Workflow Management System ● LODFlow: Use Cases ● Related Work ● Conclusion and Future Work
  • 3. Intro: A Bird’s Eye View on The Problem Creation and Maintenance of LD Datasets manual workflows applying scripts cumbersome time- consuming error- prone requiring skills
  • 4. Linked Data Workflow Management supported by a systematic way be component- oriented enabling the reuse of process facilitating the resource provenance and reproducibility ensuring the correctness supporting the evolution Intro: Solution Outline
  • 5. Linked Data Workflow Documentation Linked Data Workflow Repeatability Linked Data Workflow Management System Requirements Linked Data Workflow Planning Linked Data Workflow Execution Linked Data Workflow Reusability
  • 6. LODFlow Benefits: ● Explicitness ● Reusability ● Repeatability ● Efficiency ● Ease to use
  • 7. LODFlow: LDWPO ontology (abstract) The Linked Data Workflow Knowledge Model and Knowledge Base
  • 9. Qualis: LODFlow Use Case indirect scores for periodical papers, according 48 knowledge fields. http://qualis.capes.gov.br/webqualis/publico/pesquisaPublicaClassificacao.seam?conversationPropagation=begin use in bibliometric and scientometric studies and for ranking post- graduate programs, research proposals, or individual research scholarships.
  • 10. Qualis (cont.) ● Problem: ○ Data available only as 1 Star Data ○ Only the current version is available ○ Data is not linked to other datasets ● Solution: ○ Extracted the data from the web interface (10 years) ○ Converted Qualis to a 5-star dataset ○ Interlinked it to the DBpedia knowledge base
  • 11. Qualis: Workflow ● Create a plan for LD project ○ Planning the maintenance of LD datasets ○ Managing the lifecycle of resources ● Execute a plan ○ Maintaining the provenance and repeatability information ○ Producing the resources
  • 15. Qualis: Results ● Were executed over 10 years ● LODFlow fulfills the requirements
  • 16. Related work ● Languages such as Business Process Execution Language are adopted in technologies ● Scientific Workflow Management Systems, such as Apache Taverna and Kepler were developed
  • 17. Conclusion ● Automatization of processing LD workflows ● Preserving provenance information on (re) producing LD datasets ● Showing the benefits of explicitness, reusability, repeatability and efficiency ● Applicable in the context of the LODStack and LD Lifecycle.
  • 18. Future work: Integration with LODStack Developing a tool to integrate LODFlow to the LODStack. Improving the LDWPO with Method concepts
  • 19. Future work: New Use Cases research group extracted from a transparency portal Qualis classification set of papers extracted from Lattes CV
  • 20. Thank you for your attention! srautenberg@unicentro.br sandro.rautenberg@gmail.com We acknowledge support from CAPES/Brazil Agency as well as BMWi SAKE project.