Assessing Linked Data Mappings using Network Measures

•

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When generating a lot of WoD links automatically, data quality is a pressing issue. This presentation, and the related paper, introduce LinkQA: a network based node-centric framework to analyse the impact of linkage on the network topology and assess the quality of these links.

Technology

Assessing Linked Data Mappings using
Network Measures

Christophe Guéret, Paul Groth, Claus Stadler, Jens Lehmann

9th Extended Semantic Web Conference (ESWC)
May 29, 2012

http://latc-project.eu
ESWC - May 2012 http://aksw.org
Assessing Linked Data mappings http://www.vu.nl 1/25

The next 25+5 minutes
The impact of links in the Web of Data

Main questions
What is the impact of link creation?
Can we detect “bad” links based on their impact?
Is adding links always a good thing?

Contributions
A framework to assess the impact of links
Results for 5 metrics
ESWC - May 2012 Assessing Linked Data mappings 2/25

Is this a good or a bad link ?

ESWC - May 2012 Assessing Linked Data mappings 3/25

Measuring the Web of Data
Look at the topology using network analysis tools

Impossible to get the complete graph
Sampling of the graph focusing on specific nodes
See the bigger picture through aggregation

Build the local network around a resource

Repeat the process a sufficient number of time

ESWC - May 2012 Assessing Linked Data mappings 4/25

Network sampling process
Use SPARQL end point or de-reference the
resources to get the descriptions

ESWC - May 2012 Assessing Linked Data mappings 5/25

Aggregation of local results

Observed
Target

…

ESWC - May 2012 Assessing Linked Data mappings 6/25

Metrics
Compute local scores for a resource

Criteria
Use only the local network
Representative of a global property
Not sensitive to change of observation scale

5 metrics currently available in LinkQA

ESWC - May 2012 Assessing Linked Data mappings 7/25

What do we want to see?
Increase of connectivity within topical groups
Increase chances of finding related information

More bridges between topical groups
Improve browsing capabilities

More connectivity around hubs
Decrease the dependency upon the hubs

ESWC - May 2012 Assessing Linked Data mappings 8/25

Metric 1 – Degree
Metric
Number of edges
around the target node

Target
Power-law distribution
of values

Intuition
Presence of hubs

ESWC - May 2012 Assessing Linked Data mappings 9/25

Metric 2 – Clustering coefficient
Metric
Density of links around
the target node

Target
Increase clustering
around nodes

Intuition
Topical clusters

ESWC - May 2012 Assessing Linked Data mappings 10/25

Metric 3 – Centrality
Metric
Ratio between outgoing
and incoming links

Target
Lower the discrepancy
between the values

Intuition
Hubs are sensitive

ESWC - May 2012 Assessing Linked Data mappings 11/25

Metric 4 – SameAs chains
Metric
Number of “open”
sameAs chains

Target
No open sameAs

Intuition
Peer agreement

ESWC - May 2012 Assessing Linked Data mappings 12/25

Metric 5 – Description enrichment
Metric
Richness of resource
description

Target
Increase as possible

Intuition
“SameAsed” resources
are complementary

ESWC - May 2012 Assessing Linked Data mappings 13/25

Under the hood of LinkQA

ESWC - May 2012 Assessing Linked Data mappings 14/25
http://www.flickr.com/photos/cradlehall/5747161514

Workflow of an analysis

ESWC - May 2012 Assessing Linked Data mappings 15/25

Output of an analysis
Results on the node and aggregated scale

Per metric:
Indication of change with respect to the target
Sorted list of outlier nodes, sorted by their distance to
the target

Plus, a global ranking of nodes

=> Input for manual inspection by an expert
ESWC - May 2012 Assessing Linked Data mappings 16/25

Experimental results

ESWC - May 2012 Assessing Linked Data mappings 17/25

Global impact of links
Observe the distributions to detect bad links

ESWC - May 2012 Assessing Linked Data mappings 18/25

First evaluation
160 linking specifications for Silk, developed in
the context of LATC

6 linking specifications with manual verification of
results
50 positive links
50 negative links

Execute LinkQA with 10 samples of 50 links

ESWC - May 2012 Assessing Linked Data mappings 19/25

Results of the detection

“C” if change detected in > 50% of runs

ESWC - May 2012 Assessing Linked Data mappings 20/25

Some explanations
Low sensitivity of metrics:
Lack of data
Stable change

50/50 accuracy of detection:
Targets may not be the right ones
Sample may not be big enough
Semantics agnostic measures are less performant

ESWC - May 2012 Assessing Linked Data mappings 21/25

A closer look at the outliers
See if the outliers are necessarily bad links

ESWC - May 2012 Assessing Linked Data mappings 22/25

Second evaluation
Linking specifications for Silk, developed in the
context of LATC

All linking specifications sampled to have
45 positive links
5 negative links

Execute LinkQA five time, on five samples

ESWC - May 2012 Assessing Linked Data mappings 23/25

Rank of positive and negative links

ESWC - May 2012 Assessing Linked Data mappings 24/25

Take home message
LinkQA is a node centric approach to measure the
impact of links in the WoD network
Scalable, can be distributed

Current results show that
The 5 metrics defines are to be improved
Metrics considering Semantics perform better
The network sample seems too small
Outliers detection improves with the number of metrics

ESWC - May 2012 Assessing Linked Data mappings 25/25

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Assessing Linked Data Mappings using Network Measures

1. Assessing Linked Data Mappings using Network Measures Christophe Guéret, Paul Groth, Claus Stadler, Jens Lehmann 9th Extended Semantic Web Conference (ESWC) May 29, 2012 http://latc-project.eu ESWC - May 2012 http://aksw.org Assessing Linked Data mappings http://www.vu.nl 1/25

2. The next 25+5 minutes The impact of links in the Web of Data Main questions What is the impact of link creation? Can we detect “bad” links based on their impact? Is adding links always a good thing? Contributions A framework to assess the impact of links Results for 5 metrics ESWC - May 2012 Assessing Linked Data mappings 2/25

3. Is this a good or a bad link ? ESWC - May 2012 Assessing Linked Data mappings 3/25

4. Measuring the Web of Data Look at the topology using network analysis tools Impossible to get the complete graph Sampling of the graph focusing on specific nodes See the bigger picture through aggregation Build the local network around a resource Repeat the process a sufficient number of time ESWC - May 2012 Assessing Linked Data mappings 4/25

5. Network sampling process Use SPARQL end point or de-reference the resources to get the descriptions ESWC - May 2012 Assessing Linked Data mappings 5/25

6. Aggregation of local results Observed Target … ESWC - May 2012 Assessing Linked Data mappings 6/25

7. Metrics Compute local scores for a resource Criteria Use only the local network Representative of a global property Not sensitive to change of observation scale 5 metrics currently available in LinkQA ESWC - May 2012 Assessing Linked Data mappings 7/25

8. What do we want to see? Increase of connectivity within topical groups Increase chances of finding related information More bridges between topical groups Improve browsing capabilities More connectivity around hubs Decrease the dependency upon the hubs ESWC - May 2012 Assessing Linked Data mappings 8/25

9. Metric 1 – Degree Metric Number of edges around the target node Target Power-law distribution of values Intuition Presence of hubs ESWC - May 2012 Assessing Linked Data mappings 9/25

10. Metric 2 – Clustering coefficient Metric Density of links around the target node Target Increase clustering around nodes Intuition Topical clusters ESWC - May 2012 Assessing Linked Data mappings 10/25

11. Metric 3 – Centrality Metric Ratio between outgoing and incoming links Target Lower the discrepancy between the values Intuition Hubs are sensitive ESWC - May 2012 Assessing Linked Data mappings 11/25

12. Metric 4 – SameAs chains Metric Number of “open” sameAs chains Target No open sameAs Intuition Peer agreement ESWC - May 2012 Assessing Linked Data mappings 12/25

13. Metric 5 – Description enrichment Metric Richness of resource description Target Increase as possible Intuition “SameAsed” resources are complementary ESWC - May 2012 Assessing Linked Data mappings 13/25

14. Under the hood of LinkQA ESWC - May 2012 Assessing Linked Data mappings 14/25 http://www.flickr.com/photos/cradlehall/5747161514

15. Workflow of an analysis ESWC - May 2012 Assessing Linked Data mappings 15/25

16. Output of an analysis Results on the node and aggregated scale Per metric: Indication of change with respect to the target Sorted list of outlier nodes, sorted by their distance to the target Plus, a global ranking of nodes => Input for manual inspection by an expert ESWC - May 2012 Assessing Linked Data mappings 16/25

17. Experimental results ESWC - May 2012 Assessing Linked Data mappings 17/25

18. Global impact of links Observe the distributions to detect bad links ESWC - May 2012 Assessing Linked Data mappings 18/25

19. First evaluation 160 linking specifications for Silk, developed in the context of LATC 6 linking specifications with manual verification of results 50 positive links 50 negative links Execute LinkQA with 10 samples of 50 links ESWC - May 2012 Assessing Linked Data mappings 19/25

20. Results of the detection “C” if change detected in > 50% of runs ESWC - May 2012 Assessing Linked Data mappings 20/25

21. Some explanations Low sensitivity of metrics: Lack of data Stable change 50/50 accuracy of detection: Targets may not be the right ones Sample may not be big enough Semantics agnostic measures are less performant ESWC - May 2012 Assessing Linked Data mappings 21/25

22. A closer look at the outliers See if the outliers are necessarily bad links ESWC - May 2012 Assessing Linked Data mappings 22/25

23. Second evaluation Linking specifications for Silk, developed in the context of LATC All linking specifications sampled to have 45 positive links 5 negative links Execute LinkQA five time, on five samples ESWC - May 2012 Assessing Linked Data mappings 23/25

24. Rank of positive and negative links ESWC - May 2012 Assessing Linked Data mappings 24/25

25. Take home message LinkQA is a node centric approach to measure the impact of links in the WoD network Scalable, can be distributed Current results show that The 5 metrics defines are to be improved Metrics considering Semantics perform better The network sample seems too small Outliers detection improves with the number of metrics ESWC - May 2012 Assessing Linked Data mappings 25/25

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