CURRENTLY PATERNITY LEAVE. Notes on my work with (cultural heritage) FAIR data. Topics cover Programming, Open Science, Digital Humanities, Knowledge Graphs, Linked Data, Metadata, data catalogs, Wikidata, RDF, SPARQL and the Semantic Web.

Royal Library of Belgium

Sven Lieber

Hi everyone,  today’s summer-break edition is for anyone who likes free and open knowledge. There is a short video that explains the intriguing new
<strong>
 Wikifunctions
</strong>
project. Besides that I will talk about my experiences of creating a Wikidata page about a company, hopefully it inspires you to also contribute to free and open knowledge.

FAIR Data Digest #11

Hi everyone,  last week I told you about
<em>
 European Research Infrastructures Consortia
</em>
or ERIC in short. Today we gonna look into one of these ERICs that is active in the Cultural Heritage field. I also have to celebrate a tiny anniversary related to Wikidata and I will share a resource about FAIR Jupyter notebooks.

FAIR Data Digest #7

Dear subscriber,  Welcome to the first edition of my new weekly newsletter! Within different recurring categories I will provide updates of my work, my personal journey, and topics such as Knowledge Graphs, Linked Data, FAIR data, Open Science and many more. It is conference season!

FAIR Data Digest #1

Hi everyone,  today’s edition is about FAIR data that is not necessarily related to cultural heritage, but related to cars 🚗. We will have a look into an Open Data dataset of the Dutch government that provides data which hopefully helps me to answer some questions about
<strong>
 child safety seats
</strong>
. Statistics shown in this post come from this GitHub repository.

FAIR Data Digest #23

Hi everyone,  I hope you had a great summer. The academic year is about to start and I hope you are hungry for some knowledge :-) In today’s edition I want to introduce you to the European Open Science Cloud (EOSC).  ::: {.subscription-widget-wrap attrs=“{"url":"https://fairdata.substack.com/subscribe?","text":"Subscribe","language":"en"}” component-name=“SubscribeWidgetToDOM”}  Thanks for reading FAIR Data Digest!

FAIR Data Digest #14

Hi everyone,  this last summer-break edition ties in with the previous edition. Last week I’ve wrote over research to make
<strong>
 publication metadata
</strong>
from the free publishing service CEUR-WS
<strong>
 available in a FAIR fashion
</strong>
, such that the data can be explored.

FAIR Data Digest #13

Hi everyone,  welcome to the 3rd edition of my newsletter! Besides the fact that we have suffered the first official heat wave in Belgium this year, I have other hot information to share.

FAIR Data Digest #3

Dear subscriber,  welcome to the second edition of the newsletter and also a warm welcome to all new subscribers. It has been an interesting week. In this edition I will talk about some work updates, a one-day workshop I’ve attended last week and I have a video recommendation.

FAIR Data Digest #2

Hi everyone,  welcome to today’s edition on the the
<em>
 European Day of Languages
</em>
(Q496423).  ::: {.subscription-widget-wrap attrs=“{"url":"https://fairdata.substack.com/subscribe?","text":"Subscribe","language":"en"}” component-name=“SubscribeWidgetToDOM”}  Thanks for reading FAIR Data Digest! Subscribe for free to receive new posts and support my work.

FAIR Data Digest #17

Hi everyone,  in today’s slightly more technical edition I will focus on my recent encounters with the Linked Data query language SPARQL. Many of you may know it as a language to retrieve data (possibly from Wikidata). I mainly use it for a project where I recently found some performance issues that could be resolved by either rewriting the query or changing the approach.

FAIR Data Digest #22

Hello everyone,  welcome to today’s Halloween edition about
<em>
 data anti-patterns
</em>
that hopefully will scare you so much you don’t do them :-) Things you better avoid when aiming for FAIR data. Anti patterns?

FAIR Data Digest #20

Hi everyone,  greetings from Karlsruhe in Germany where I am attending a conference about research data infrastructure at the moment.

FAIR Data Digest #15

Hi everyone,  I’m on vacation now, but thanks to pre-scheduling you won’t miss out FAIR data updates! Today I want to share with you a research paper in which the authors report on the creation of large amounts of FAIR data which they host on Wikidata.

FAIR Data Digest #12

Hi everyone,  it has been a while since we talked about research infrastructures. Many of them might sound abstract or just like super specialized app stores. But today we have a brief look into something very tangible: heritage objects that are analyzed by instruments or are digitized in other forms. There is lots of diverse data in Heritage Science. ❓ FAIR Buzzword Bingo: what is E-RIHS?

FAIR Data Digest #21

Hi everyone,  welcome back to today’s edition in which I share a work update related to bibliographic data and provide information to an upcoming interesting talk. ::: {.subscription-widget-wrap attrs=“{"url":"https://fairdata.substack.com/subscribe?","text":"Subscribe","language":"en"}” component-name=“SubscribeWidgetToDOM”}  Thanks for reading FAIR Data Digest! Subscribe for free to receive new posts and support my work.

FAIR Data Digest #19

Hi everyone,  this edition starts with two announcements before it dives into the topic of software engineering skills for data science. This newsletter started as a
<strong>
 weekly newsletter
</strong>
in which I shared topics around FAIR data and updates about my work. Selecting one or more topics each week is fun and helps myself to
<em>
 summarize
</em>
and
<em>
 understand
</em>
topics better.

FAIR Data Digest #18

Hi everyone,  welcome to another summer-break edition. This time with a webinar recording about persistent identifiers for FAIR data and news about data cataloging with DCAT both in Europe and the US.  ::: {.subscription-widget-wrap attrs=“{"url":"https://fairdata.substack.com/subscribe?","text":"Subscribe","language":"en"}” component-name=“SubscribeWidgetToDOM”}  Thanks for reading FAIR Data Digest!

FAIR Data Digest #10

Hi everyone,  greetings to one of our summer editions! Whether you're on vacation, just back, or about to head off, I've got some interesting content to share with you.

FAIR Data Digest #9

Hi everyone,  in today’s edition I will try to explain what DARIAH / CLARIAH is and what they do in the context of FAIR data. I am also sharing a video of some recent presentations about Wikipedia from the Wikimedia Research Showcase. ::: {.subscription-widget-wrap attrs=“{"url":"https://fairdata.substack.com/subscribe?","text":"Subscribe","language":"en"}” component-name=“SubscribeWidgetToDOM”}  Thanks for reading FAIR Data Digest!

FAIR Data Digest #8

Hi everyone,  if you are a researcher and you want to follow the FAIR data principles you are not left alone. In today’s edition I will try to explain what ERIC is and what they have to do with FAIR data. As for work updates: I was on a small camping vacation in France, so there are no work updates, but I came back with many ideas for the future!

FAIR Data Digest #6

Hi everyone,  did you ever wonder how FAIR data is put into practice? This week I went down the rabbit hole and what I brought back is the start of a new series to
<strong>
 unravel the many FAIR data initiatives
</strong>
. There are also some good news for (Belgian) FAIR data in my work update!

FAIR Data Digest #5

Hi everyone,  this week it’s all about hands-on! I will talk about a webinar on trying to fix quality issues in Wikidata by using its ontology. Additionally I will share a few resources around basics and advanced uses of the query language SPARQL that is used to query Linked Data, for example from Wikidata.

FAIR Data Digest #4

Hi everyone,  as promised, today you will hear more about the research data infrastructure conference where I and around
<strong>
 680 other people
</strong>
attended last week in Karlsruhe, Germany. Grab a cup of coffee of tea and enjoy today’s edition!

FAIR Data Digest #16

FAIR Data Digest

Hi everyone,

this last summer-break edition ties in with the previous edition. [Last
week](https://fair-data-digest.org/archive/12) I've wrote over research
to make **publication metadata** from the free publishing service
CEUR-WS **available in a FAIR fashion**, such that the data can be
explored. Today I focus on a smaller initiative to make metadata of **50
papers** available, as well as research to make metadata about
astonishing **249 million publications** available! Both are necessary.

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🔍 Usually there are many players in a data ecosystem. Anyone of those
players can contribute towards FAIR data. Recently, the organizers of
the upcoming SEMANTiCS conference
([Q59916981](https://www.wikidata.org/wiki/Q59916981)) wrote a blog post
about how they embrace **Open Science best practices**: with a
semi-automatic pipeline and manual curation. I briefly talk about their
recent blog post and link it for you.

🧪 *What's the trend of publications around a certain topic for an
institution?* Obtaining such strategically important information is
cumbersome. Information must be curated or alternatively must be
retrieved via paid services from publishing houses. But those data silos
might be difficult to access or may just be discontinued, such as the
Microsoft Academic Graph
([Q62056662](https://www.wikidata.org/wiki/Q62056662))
([source](https://www.nature.com/nature-index/news/microsoft-academic-graph-discontinued-whats-next)).
In today's Science Spotlight I present a paper about an operative **open
data platform** that makes **metadata of 249 million publications
available under the open license CC0 (thus anyone can freely use their
data)**. I will summarize their incredible work and show that nobody's
perfect.

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# 🔍 Insights: Open Science best practices at SEMANTiCS conference {#insights-open-science-best-practices-at-semantics-conference}

<div>

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</div>

Let's start small. There are many players in the academic world ranging
from conferences organized by researchers to publishers, academic
institutions or funding bodies. Anyone of those players can contribute
to a FAIR data ecosystem.

Recently the organizers of the SEMANTiCS conference announced how they
*eat their own dog food* and embrace Open Science best practices. They
created and published FAIR data about their 50 accepted papers,
involving automatic processing and manual curation.

This allowed them to create **insightful statistics**. For example,
anyone can see that 26 out of the 50 accepted papers are resource
papers, meaning that they present a *resource* such as a dataset or a
tool that was deemed relevant by the peer-reviewing. Thanks to the
statistics, interpretations can be made. According to the organizers, it
does **not seem to be widespread practice to share persistent
identifiers for code** - which becomes apparent thanks to the
statistics.

Other Semantic-Web related conferences such as ESWC
([Q17012957](https://www.wikidata.org/wiki/Q17012957)) also publish FAIR
metadata
([source](https://2022.eswc-conferences.org/conference-metadata/)). If
more conferences would do this, we would get high quality metadata **at
the source** which surely would improve the data quality of downstream
applications and data aggregation.

So far they use the data as found in the conference management system
EasyChair ([Q1278323](https://www.wikidata.org/wiki/Q1278323)).
Unfortunately, there are no author identifiers which makes downstream
tasks more difficult due to ambiguous names. See also the following item
in the newsletter to see why this could become a problem. Curious? Check
out their short blog post to learn about their semi-automatic workflow
with manual curation.

[Read the SEMANTiCS blog
post](https://semantics-org.github.io/page/news?page=2023-08-10){.button
.primary}

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</div>

# 🧪 Science Spotlight: Metadata of 249 million publications in SemOpenAlex {#science-spotlight-metadata-of-249-million-publications-in-semopenalex}

<div>

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</div>

Staying on top of the research game is difficult, because millions of
articles are published every year. Whether you look for a simple
information or more analytical data, finding it might be relevant for
strategic decisions. More than that, all the data-driven services we are
used to nowadays, rely on high quality data. **Believe it or not, since
recently you can access metadata about 249 million publications under
the open CC0 license.**

Since the de-continuation of the Microsoft Academic Graph, the
[OpenAlex](https://openalex.org/) initiative
([Q107507571](https://www.wikidata.org/wiki/Q107507571)) makes large
amounts of metadata about scientific publications freely available.
However, as a reader of this newsletter you probably know that *having
data* and *having FAIR data* makes a huge difference! (Spoiler: the
latter is better).

A paper that will be presented at the upcoming *International Semantic
Web Conference 2023*
([Q119153957](https://www.wikidata.org/wiki/Q119153957)), or in short
ISWC, presents SemOpenAlex! A web platform and data dump that is created
monthly on top of the OpenAlex data. It makes their data truly FAIR by
following the Linked Open Data principles.

## A publicly available resource with many use cases

As outlined by the authors, the presented SemOpenAlex Knowledge Graph
that can be accessed and queried by anyone has several use cases.

- Scholarly Big Data analytics

- Large-Scale scientific impact quantification

- Scholarly search and recommender systems

- Semantic scientific publishing

- Research project management and modeling

- Groundwork for scientific publishing in the future

- Knowledge-guided language models

- Benchmarking

## Human-in-the-loop seems necessary

I looked for myself in their database and found 3 entries (see image
below). The first match is the most comprehensive record covering almost
all of my publications. The two others are duplicates where each is
linked to only one publication. Funnily, it is the same publication
linked to both duplicates, yet also that publication is a duplicate.
**And even more ironically, the duplicate is a publication about Linked
Open Data validity!**

::: {.captioned-image-container}
<figure>
<a
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data-component-name="Image2ToDOM"></a>
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<div class="image-link-expand">
<img
src="data:image/svg+xml;base64,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"
class="lucide lucide-maximize2" />
</div>
</div>
<figcaption>Finding myself three times in SemOpenAlex: automatic
processing is not perfect, manual curation is often
necessary</figcaption>
</figure>
:::

I would love to signal the duplicates such that they can be merged and
that the quality can be improved. Unfortunately in the current setting
of the platform this is not possible. I guess this is because they just
use data from OpenAlex, so I would have to figure out how to correct my
data there at the source. Anyway, OpenAlex is also a data aggregator
which makes it more difficult. This can probably be avoided when **using
unique author identifiers at all time** (an issue also apparent at the
SEMANTiCS data outlined in the previous newsletter item).

Are you intrigued to learn more about SemOpenAlex? Check out their
openly available paper [DOI:
10.48550/arXiv.2308.03671](https://doi.org/10.48550/arXiv.2308.03671) or
dive into their data yourself by using their web application!

[Explore their data yourself](https://semopenalex.org/){.button
.primary}

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That's it for this week of the FAIR Data Digest. I hope you found the
content interesting. Don't forget to share or subscribe. See you next
week!

Sven

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