1.
Motivation
Data on the Web
Some eyecatching opener illustrating growth and or diversity of web data
Profiling & Exploration of Linked Datasets
Stefan Dietze, Besnik Fetahu, Davide Taibi
L3S Research Center, DE,
@stefandietze,
http://purl.org/dietze
Stefan Dietze 12/03/14

2.
Data curation and dataset profiling
LinkedUp
Dataset Catalog
Stefan Dietze 12/03/14
 Catalog of data (LinkedUp
Catalog): classification of datasets
according to resource types,
disciplines/topics, data quality,
accessability, etc
 Infrastructure for
distributed/federated querying
describes
 Which datasets are useful & trustworthy for case
XY (eg „learning about the solar system“) ?
 Which topics (eg „Astronomy“) are covered by
dataset X?
 Which datasets offer videos (slides, publications,
statistics etc)?

3.
LinkedUp Data Catalog
in a nutshell http://datahub.io/group/linked-education
http://data.linkededucation.org/linkedup/catalog/
 RDF (VoID) dataset catalog: browse &
query distributed datasets
 Live information about endpoint
accessibility
 Federated queries using type
mappings
Stefan Dietze 12/03/14

4.
db:Astro. Objects
Extracting Topic Profiles of Linked Datasets
Dataset
Metadata
Stefan Dietze 12/03/14
Schema mappings
BIBO
AAISO
FOAF
contains
Entity disambiguation
Topic profile extraction
db:Astronomy
db:Astro. Objects
LinkedUp
Dataset Catalog
yov:Video
po:Programme
BBC Programme
<po:Programme …>
<po:Series>Wonders of the Solar System</.>
<po:Actor>Brian Cox</…>
</po:Programme…>
<yo:Video …>
<dc:title>Pluto & the
Dwarf Planets</dc:title>
…
</yo:Video…>
Yovisto Video
bibo:Fil
bibo:Fi
bibo:Film

5.
What’s all the data about: exploring topics of LOD
in a nutshell http://data-observatory.org/lod-profiles/
Stefan Dietze 12/03/14
 Visualisation & exploration of dataset-topic-graph
(datasets, topics, relationships)
 Includes all responsive datasets of LOD Cloud
A Scalable Approach for Efficiently Generating
Structured Dataset Topic Profiles, Fetahu, B., Dietze,
S., Nunes, B.P., Cassanova M., Nejdl, W. (2014), 11th
Extended Semantic Web Conference, ESWC2014,
Greece, May 2014.

6.
Stefan Dietze 12/03/14
dbp:Category:Royal_Medal_winners
dbp:Category:1955_births
dbp:Category:People_from_London
dbp:Category:Buzzwords
dbp:Category:Web_Services
dbp:Category:HTTP
dbp:Category:Unitarian_Universalists
dbp:Category:World_Wide_Web
What have these categories in common?

7.
Stefan Dietze 12/03/14
Diversity of category profile for a single paper
Berners-Lee, Tim; Hendler, James, Ora Lassila (2001). "The Semantic Web".
Scientific American Magazine.
person
document
dbp:Tim_Berners-Lee
dbp:Category:1955_births
dbp:Category:People_from_London
dbp:Category:Buzzwords
dbp:Semantic_Web
dbp:Category:Semantic_Web
dbp:Category:Web_Services
dbp:Category:HTTP
dbp:Category:Unitarian_Universalists
first-level categories (dcterms:subject)
dbp:Category:World_Wide_Web
dbp:Category:Royal_Medal_winners

8.
 DBpedia category graph not an ideal “topic” vocabulary:
 Broad and noisy
 “Categories” vs “topics” (for capturing disciplines, thesauri
like UNESCO Thesaurus seem better suited)
 Lack of clear hierarchy: graph, not a tree
 Mixing categories across resource types (document, person
etc) creates “perceived noise”
 But: broadness is useful as general vocabulary for
categorisation of all sorts of resource types
Stefan Dietze 12/03/14
Dataset profiling: some lessons learned

9.
Stefan Dietze 12/03/14
http://data-observatory.org/led-explorer/
 Type specific views on datasets/
categories (ie “topics”)
 “Document” (foaf:document)
 “Person “ (foaf:person)
 “Course” (aaiso:course)
 Currently applied to datasets in
LinkedUp Catalog only (as
schema mappings already
available here)
More precise profiles of educational datasets

10.
Thank you!
12/03/14 10Stefan Dietze
http://data-observatory.org/led-explorer/
http://data-observatory.org/lod-profiles/