jurion quality assurance by christian dirschl
TRANSCRIPT
Agenda
• JURION Quality Assurance Trial 1• JURION IPG Use Case• Next steps: „Schema Change“ Use Case• Summary
2
Example errors in data which we would like to find
• Relations-based: Same person for same company as representative and oversight at any moment in time.
• Data-based:– Do shares sum up to partnership capital value at
every moment in time– Did a company publish multiple annual reports
• Mixed: Are there multiple shareholders if company is labeled as „Sole Shareholder”.
JURION Content Pipeline
PCI
Metadata
Externalmeta data
SourcesCrawler;Importer XML Metadata extraction
and enrichment
Linking/patternrecogn. XML
CMS MetaData DB
MetaDataeditor
ThesaurusManager
PCI
Indexer
SQL DB
ProprietaryData
Sources
Search
Conceptual Data model
Retrieval/Search/Application
End user App
Content Management
ModelandDB
QualityCheck RDF
Ontology
12
• Break up silos of isolated lifecycles; have a holistic view on overall process and start optimizing on this basis
• Use LOD technology to improve data quality• Build models of your lifecycles where you need them for
practical reasons (e.g. interaction points) • Re-use standards wherever possible• Solve problems where they come from, not where they
show up
• Never underestimate the complexity challenge that comes with mass data from different sources in different quality created for different purposes
• Don’t look for a generic solution. Take an iterative and lean approach instead
Do‘s
Don‘ts
Summary
Christian [email protected]://solutions.wolterskluwer.com/blog/author/christian-dirschl/
ALIGNED Projecthttp://aligned-project.eu
Jurion Plattformhttp://www.jurion.de
ALIGNED Projecthttp://aligned-project.eu