https://2016.semantics.cc/satellite-events/data-quality-tutorial

1. 1Quality
Management
in PoolParty
Helmut Nagy
COO, Semantic Web
Company

2. Problem
statement
▸ Data consistency
▹ PoolParty expects data to confirm to
certain constraints.
▹ User can import arbitrary RDF data.
▸ Schema based constraints
▹ Data published without schemata or
with a minimally specified schema.
▹ Interpretation/usage of schemata
varies widely.
2

3. Challenges
▸ Find a way to formulate constraints in a
easy maintainable way.
▸ Find a way to express constraints in a
unified way for usage throughout the
system.
▸ Check conformance of data to specific
schemata.
3

4. Quality
Management -
Pre 5.5
4 ▸ No validation during import
▹ Data can fail to display
▹ Data can cause unexpected
behaviour
▹ Lead to/reflect errors in the
application.
▸ Quality checks based on qSKOS

5. Quality
Management -
Pre 5.5
Demo
5

6. Quality
Management -
PP 5.5
Import
Validation
6 ▸ RDF Validation has been integrated.
▹ Checks are defined in RDF.
▹ Repair strategies and other
metadata are also defined as RDF.
▸ In a first step 15 checks have been
integrated.
▸ Prototypes using RDF-Unit and SHACL
have been done.

7. Quality
Management -
PP 5.5
Architecture
7

8. 8Quality
Management -
PP 5.5
Demo

9. Outlook
9

10. Outlook
10 ▸ Support validation of other RDF data and
schemata (Ontologies)
▸ Support validation during data
transformations (UnifiedViews)
▸ Support validation of data in different
places (built in store, remote store).
▸ Use a declarative approach (RDF Shapes)
▹ Integrate RDF-Unit
▹ Use SHACL
▹ Better to understand, maintain, reuse

11. CONNECT
Helmut Nagy
COO, Semantic Web Company
▸ h.nagy@semantic-web.at
▸ https://at.linkedin.com/in/helmutnagy
▸ https://twitter.com/semwebcompany
▸ https://blog.semantic-web.at/
11
© Semantic Web Company - http://www.semantic-web.at/ and http://www.poolparty.biz/