JudaicaLink: Linked Data in the Jewish Studies FID

WISS Research Group | JudaicaLink: Linked Data in the Jewish Studies FID - EVA/MINERVA 2017 - Nov 14th, 2017 - Jerusalem
JudaicaLink
Linked Data in the Jewish Studies FID
Kai Eckert
http://www.judaicalink.org
1

FID Jewish Studies / Israel Studies
Creation of a specialized information service
(Fach-Informations-Dienst) for the domain of Jewish
studies and Israel Studies.
Our part:
● Metadata integration and enrichment.
● Multilingual data matching.
2
Funding by
Consortium

Portal of Jewish Studies
Goals:
● Create a central access point
● Offer high performance information
infrastructure
And also,
● Contextualize the digital Judaica
collections
● Enrich the metadata
● Connect different data sources as
Linked Open Data
3

The Portal
4
http://umber.ub.uni-frankfurt.de/judaica/ (Beta version, not yet officially launched!)

WISS Research Group | JudaicaLink: Linked Data in the Jewish Studies FID - EVA/MINERVA 2017 - Nov 14th, 2017 - Jerusalem 5

Goals:
infrastructure
And also,
collections
Linked Open Data
6

Re-Transliteration
7
● Automatic Retro-Conversion
of Romanized Hebrew Text
● Improve search facilities
for Hebrew speakers
● Needed to match data
cross-lingually
Aaron Christianson

Retro-Conversion of Romanized Hebrew Text
lĕqahaḥ t teḥ qst ʿivrî bĕ-taʿătîq lātîḥnî
‫עבוריות‬ ‫לאותיות‬ ‫אותו‬ ‫ולהפוך‬
8

‫המלא‬ ‫הסיפור‬
‫ֵא‬‫ל‬ ָ‫מ‬ַ‫ה‬ ‫רּ‬ ‫ו‬ִ‫ס‬ַ‫ה‬
9

Problem Statements
● No Hebrew Script until 2011
● Multiple standards of Romanization
● Ambiguities: Same romanized character can refer to
several Hebrew letters.
● Data imported from other catalogs
● The transliterations contain errors
(yes, even librarians make - rare - mistakes)
10

The Plan
1. Generate all possible original
forms in a “stupid” way.
2. Match the output against known
Hebrew names / titles.
3. Use the verified matches to
train a statistical model on the
word/phrase level.
11

Goals:
infrastructure
And also,
collections
Linked Open Data
12

Contextualization of Digital Resources
● Find relevant data sources
● Find matching resources
● Extract information
● Add information to
library collection
13
Maral Dadvar

It’s all about Labels!
● Labels (Strings) are the first thing
we search to generate matching
candidates.
● Every additional label for a resource is
a possible new entry point to create
a connection.
● Caveat: More labels also create
more false positives. Further evidence
is needed to establish a link.
14

● Make unstructured data
sources like online
encyclopedia available
as structured data
● Identify and collect
relevant subsets of
general-purpose
knowledge bases like
DBpedia
● To function as a single
hub for the
contextualization
process
16

Main Tasks
1. Find new resource descriptions - with labels!
2. Find new labels (and other data) for known resources.
3. Find connections and duplicates within known resources.
4. Make the data available for others to contextualize.
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Example 1: YIVO Encyclopedia
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What Data can we find?
● A title
● Describing text
● Links in texts
"Surface form" => Concept
● Pictures
● Description of pictures
19

Making use of the Surface Forms
Minsk article links to "Poland before 1795" calling it
"Polish-Lithuanian Commonwealth".
"Polish-Lithuanian Commonwealth" is a subsection
of "Poland before 1795" in the main article "Poland".
So is "Demography"…
Surface forms are evidence for labels.
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Example 2: Biographisches Handbuch der Rabbiner
● The Biographisches Handbuch der Rabbiner is an online encyclopedia
provided by the Salomon L. Steinheim-Institute for German-Jewish history at
the University of Duisburg-Essen, edited by Michael Brocke and Julius
Carlebach.
● The goal of this encyclopedia is to be a complete directory of all rabbis who
lived and worked in or originated from German-speaking areas since the age
of enlightenment.
● http://www.steinheim-institut.de/wiki/index.php/Biographisches_Handbuch_de
r_Rabbiner_%28BHR%29
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Available
as PDF.
22

Some notes about PDF Sources
● PDF is great to keep the visual layout of a text across
systems.
● In all other aspects, in particular regarding the access to
the content, it is horrible.
● Digital-born PDFs (as in this case) are PDFs that have
been created directly by the authoring software.
● Even worse: PDFs created from scans (with OCR).
23

Biographisches Portal der Rabbiner
Gladly some people at Steinheim Institute created a database from the handbook:
http://www.steinheim-institut.de:50580/cgi-bin/bhr#i0001
This URL above is shown in the browser when you view the entry on Aach, Löb.
Great stuff:
● Semi-structured form of the entry
● “Link” to the PDF by means of volume and page number
● Reference to the number of the entry as it is used in the PDF.
● A GND number!!!
Not so great:
● We can not link to the database as the link above does not resolve to the
article.
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Solution
The solution actually was already implemented:
There is an undocumented way to address an entry:
http://steinheim-institut.de:50580/cgi-bin/bhr?id=1
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Example 3: DBpedia
Generation of a DBpedia subgraph.
1. Focused Crawling of data sources
a. identify “relevant” resources
b. extract “relevant” information
2. Find matches in the whole dataset
a. extract “relevant” information
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Interlinking
The more data sources we have, the better we can use them to support the linking
process.
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Architecture and Deployment
Triple store and SPARQL endpoint: Apache Jena Fuseki
Linked Data frontend (URI dereferencing, HTML Views): Pubby (DM2E version)
Static HTML pages of the website: Hugo
Versioning and management: GitHub
Search Access: Elasticsearch (planned)
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Dataset Description in Markdown
with Metadata Frontmatter
+++
author = "Kai Eckert"
title = "Yivo Encyclopedia"
website = "http://www.yivoencyclopedia.org"
example = "http://data.judaicalink.org/data/yivo/Moscow"
graph = "http://data.judaicalink.org/data/yivo"
loaded = true
[[files]]
url = "http://data.judaicalink.org/dumps/yivo/current/yivo.n3.gz"
description = "Extraction from YIVO Encyclopediae"
+++
The YIVO Encyclopedia of Jews in Eastern Europe, courtesy of the YIVO Institute of
Jewish Research, NY.

...
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The whole website is maintained via GitHub
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Every new commit gets pushed to the web server
Via the static site generator Hugo, all HTML pages are generated.
32
+++
author = "Kai Eckert"
title = "Yivo Encyclopedia"
website = "http://www.yivoencyclopedia.org"
example =
"http://data.judaicalink.org/data/yivo/Moscow"
graph = "http://data.judaicalink.org/data/yivo"
loaded = true
[[files]]
url =
"http://data.judaicalink.org/dumps/yivo/current/
yivo.n3.gz"
description = "Extraction from YIVO
Encyclopediae"
+++
The YIVO Encyclopedia of Jews in Eastern Europe,
courtesy of the YIVO Institute of Jewish
Research, NY.

...

Every new commit gets pushed to the web server
A Python script parses the metadata of the pages
and loads and unloads the datasets automatically.
Advantages:
● No one needs access to the server.
● Write access to the data is easily done via GitHub.
● Data dumps of all datasets are always available.
● Description, dumps and loaded data are always synchronous.
● History of the datasets is maintained (and the dumps)
● Mistakes can easily be reverted by going back to an earlier commit.
33

Thank you.
http://slideshare.net/kaiec
http://www.wisslab.org
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JudaicaLink: Linked Data in the Jewish Studies FID

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JudaicaLink: Linked Data in the Jewish Studies FID