Tag: Open Data

Wikidata in the Classroom and the WikiCite project

The following post was presented by Wikimedian in Residence, Ewan McAndrew, at the Repository Fringe Conference 2018 held on 2nd & 3rd July 2018 at the Royal Society of Edinburgh.


Hi, my name’s Ewan McAndrew and I work at the University of Edinburgh as the Wikimedian in Residence.

My talk’s in two parts;

The first is part is on teaching data literacy with the Survey of Scottish Witchcraft database and Wikidata.

Contention #1:  since the City Region deal is there is a pressing need for implementing data literacy in the curriculum to produce a workforce equipped with the data skills necessary to meet the needs of Scotland’s growing digital economy and that this therefore presents a massive opportunity for educators, researchers, data scientists and repository managers alike.

Wikidata is the sister project of Wikipedia and it the backbone to all the Wikimedia projects, a centralised hub of structured, machine-readable, multilingual linked open data. An introduction to Wikidata can be found here.

I was invited along with 13 other ‘problem holders’ to a ‘Data Fair’ on 26 October 2017 hosted by course leaders on the Data Science for Design MSc. We were each afforded just five minutes to pitch a dataset for the 45 students on the course to work on in groups as a five week long project.

The ‘Data Fair’ held on 26 October 2017 for Data Science for Design MSc students. CC-BY-SA, own work.

Two groups of students were enthused to volunteer to help surface the data from the Survey of Scottish Witchcraft database, a fabulous piece of work at the University of Edinburgh from 2001-2003 chronicling information about accused witches in Scotland from the period 1563-1736, their trials and the individuals involved in those trials (lairds, sheriffs, prosecutors etc.) which remained somewhat static and unloved in an Microsoft Access database since the project concluded in 2003. So students at the 2017 Data Fair were invited to consider what could be done if the data was exported into Wikidata with attribution, linking back to the source database to provide verifiable provenance, given multilingual labels and linked to other complementary datasets? Beyond this, what new insights & visualisations of the data could be achieved?

There were several areas of interest: course leaders on the Data Science for Design MSc were keen for the students to work with ‘real world’ datasets in order to give them practical experience ahead of their dissertation projects.

 “A common critique of data science classes is that examples are static and student group work is embedded in an ‘artificial’ and ‘academic’ context. We look at how we can make teaching data science classes more relevant to real-world problems. Student engagement with real problems—and not just ‘real-world data sets’—has the potential to stimulate learning, exchange, and serendipity on all sides, and on different levels: noticing unexpected things in the data, developing surprising skills, finding new ways to communicate, and, lastly, in the development of new strategies for teaching, learning and practice.”

Towards Open-World Scenarios: Teaching the Social Side of Data Science by Dave Murray Rust, Joe Corneli and Benjamin Bach.

Beyond this, there were other benefits to the exercise. Tim Berners-Lee, the inventor of the Web, has suggested a 5-star deployment scheme for Open Data (illustrated in the picture and table below). Importing data into Wikidata makes it 5 star data!

By Michael Hausenblas, James G. Kim, five-star Linked Open Data rating system developed by Tim Berners-Lee. (http://5stardata.info/en/) [CC0], via Wikimedia Commons
Number of stars Description Properties Example format
make your data available on the Web (whatever format) under an open license
  • Open license
★★ make it available as structured data (e.g., Excel instead of image scan of a table)
  • Open license
  • Machine readable
★★★ make it available in a non-proprietary open format (e.g., CSV instead of Excel)
  • Open license
  • Machine readable
  • Open format
★★★★ use URIs to denote things, so that people can point at your stuff
  • Open license
  • Machine readable
  • Open format
  • Data has URIs
★★★★★ link your data to other data to provide context
  • Open license
  • Machine readable
  • Open format
  • Data has URIs
  • Linked data

Importing data into Wikidata makes it 5 star data!

Open data producers can use Wikidata IDs as identifiers in datasets to make their data 5 star linked open data. As of June 2018, Wikidata featured in the latest Linked Open Data cloud diagram on lod-cloud.net as a dataset published in the linked data format containing over 5,100,000,000 triples.

Over a series of workshops, the Wikidata assignment also afforded the students the opportunity to develop their understanding of, and engagement with, issues such as: data completeness; data ethics; digital provenance; data analysis; data processing; as well as making practical use of a raft of tools and data visualisations. It also motivated student volunteers to surface a much-loved repository of information as linked open data to enable further insights and research. A project that the students felt proud to take part in and found “very meaningful”. (The students even took the opportunity to consult with professors of History at the university in order to gain even more of an understanding of the period in which these witch trials took place, such was their interest in the subject).

Feedback from students at the conclusion of the project included:

  • “After we analysed the data, we found we learned the stories of the witches and we learned about European culture especially in the witchhunts.”
  • “We had wanted to do a happy project but finally we learned much more about these cultures so it was very meaningful for us.”
  • “In my opinion, it’s quite useful to put learning practice into the real world so that we can see the outcome and feel proud of ourselves… we learned a lot.”
  • “Thank you for inviting us and appreciating our video. It’s an unforgettable experience in my life. Thank you so much.”

As a  result of the students’ efforts, we now have 3219 items of data on the accused witches in Wikidata (spanning 1563 to 1736). We also now have data on 2356 individuals involved in trying these accused witches. Finally we have 3210 witch trials themselves. This means we can link and enrich the data further by adding location data, dates, occupations, places of residence, social class, marriages, and penalties arising from the trial.

The fact that Wikidata is also linked open data means that students can help connect to and leverage from a variety of other datasets in multiple languages; helping to fuel discovery through exploring the direct and indirect relationships at play in this semantic web of knowledge.


Descendents of King James VI and I, king during union of English and Scottish crowns

And we can see an example of this semantic web of related entities, or historical individuals in this case, here in this visualisation of the descendants of King James I of England and James VI of Scotland (as shown in the pic above but do click on the link for a live rendering).

We can also see the semantic web at play in the below class level overview of gene ontologies (505,000 objects) loaded into Wikidata, and linking these genes to items of data on related proteins and items of data on related diseases, which, in turn, have related chemical compounds and pharmaceutical products used to treat these diseases. Many of these datasets have been loaded into Wikidata, or are maintained by, the GeneWiki initiative – around a million Wikidata items of biomedical data – but, importantly, they are also leveraging from other datasets imported from the Centre for Disease Control (CDC) among other sources. This allows researchers to add to and explore the direct and, perhaps more importantly, the indirect relationships at play in this semantic web of knowledge to help identify areas for future research.


Using Wikidata as an open, community-maintained database of biomedical knowledge – CC-BY: Andrew Su, Professor at The Scripps Research Institute.

Which brings me onto…

Contention #2 – Building a bibliographical repository: the sum of all citations

Sharing your data to Wikidata, as a linking hub for the internet, is also the most cost-effective way to surface your repository’s data and make it 5 star linked open data. As a centralised hub for linked open data on the internet, it enables you to leverage from many other datasets while you can still have  your own read/write applications on top of Wikidata. (Which is exactly what the GeneWiki project did to encourage domain experts to contribute to knowledge gaps on Wikidata through providing a user-friendly read/write interface to enable the “consumption and curation” of gene annotation data using the Wiki Genome web application).

Within Wikidata, we have biographical data, geographical data, biomedical data, taxomic data and importantly, bibliographic data.

The WikiCite project are building a bibliographic repository of sources within Wikidata.

“How does the Wikimedia movement empower individuals to assess reliable sources and arm them with quality information so they can make decisions based in facts? This question is relevant not only to Wikipedia users​ but to consumers of media around the globe. Over the past decade, the Wikimedia movement has come together to answer that question. Efforts to design better ways to support sourcing have begun to coalesce around Wikidata – the free knowledgebase that anyone can edit. With the creation of a rich, human-curated, and machine-readable knowledgebase of sources, the WikiCite initiative is crowdsourcing the process of vetting information​ and its provenance.” – WikiCite Report 2017

Wikidata tools can be used to create Wikidata items on scholarly papers automatically from scraping source metadata from:

  • DOIs,
  • PMIDs,
  • PMCIDs
  • ORCIDs (NB: Multiple items of data can be created simultaneously to represent multiple scholarly papers using one ORCID identifier input in the Orcidator tool).

Indeed, 1 out of 4 items of data in Wikidata represents a creative work. Wikidata currently includes 10 million entries about citable sources, such as books, scholarly papers, news articles and over 75 million author string statements and 84 million citation links in Wikidatas between these authors and sources. 17 million items with a Pubmed ID and 12.4 million items with a DOI.

Mike Bennett, our Digital Scholarship Developer at the University of Edinburgh, is working to develop a tool to translate the Edinburgh Research Archives’ thesis collection data from ALMA into a format that Wikidata can accept but there are ready-made tools that Wikidatans have developed that will automatically create a Wikidata item of data for scholarly papers scraping the source metadata from DOIs, Pubmed IDs and ORCID identifiers, allowing for a bibliographic record of scholarly papers and their authors to be generated as structured, machine-readable, multilingual linked open data.

Why does this matter?

Well…​the Initiative for Open Citations (I4OC) is a new collaboration between scholarly publishers, researchers, and other interested parties to promote the unrestricted availability of scholarly citation data. Over 150 publishers have now chosen to deposit and open up citation data. As a result, the fraction of publications with open references has grown from 1% to more than 50% out of 38 million articles with references deposited with Crossref.

Citations are the links that knit together our scientific and cultural knowledge. They are primary data that provide both provenance and an explanation for how we know facts. They allow us to attribute and credit scientific contributions, and they enable the evaluation of research and its impacts. In sum, citations are the most important vehicle for the discovery, dissemination, and evaluation of all scholarly knowledge.”

Once made open, the references for individual scholarly publications may be accessed within a few days through the Crossref REST API.  Open citations are also available from the OpenCitations Corpus that is progressively and systematically harvesting citation data from Crossref and other sources. An advantage of accessing citation data from the OpenCitations Corpus is that they are available i n machine-readable RDF format which is systematically being added to Wikidata.

Because this is data on scholars, scholarly papers and citations is stored as linked data on Wikidata, the citation data can be linked to, and leverage from, other complementary datasets enabling the direct and indirect relationships to be explored in this semantic web of knowledge.

This means we can parse the data to answer a range of queries such as:

  • Show me all works which cite a New York Times article/Washington Post article/Daily Telegraph article etc. (delete as appropriate).
  • Show me the most popular journals cited by statements of any item that is a subclass of economics/archaeology/mathematics etc. (delete as appropriate).
  • Show me all statements citing the works of Joseph Stiglitz/Melissa Terras/James Loxley/Karen Gregory etc. (delete as appropriate).
  • Show me all statements citing journal articles by physicists at Oxford University in 1960s/1970s/1980s etc. (delete as appropriate).
  • Show me all statements citing a journal article that was retracted.

And much more besides.

Screengrab of the Scholia profile for the developmental psychologist, Uta Frith, generated from the structured linked data in Wikidata.


Like the WikiGenome web application already mentioned, other third party applications can be built with user-friendly UIs to read/write from Wikidata. For instance, the Scholia Web service creates on-the-fly scholarly profiles for researchers, organizations, journals, publishers, individual scholarly works, and research topics. Leveraging from information in Wikidata, Scholia displays information on total number of publications, co-authors, citation statistics in a variety of visualisations. Another way of helping to demonstrate the impact and reach of your research.

Citation statistics for developmental psychologist Uta Frith, visualised on the Scholia web service and generated from the citation data in Wikidata.
Co-author graph for Polly Arnold, Professor of Chemistry at the University of Edinburgh in the School of Chemistry visualised in the Scholia Web Service and generated from bibliographic data in Wikidata. Professor Arnold is the Crum Brown Chair of Chemistry at the University of Edinburgh.

To  conclude, the many benefits and power of linked open data to aid the teaching of data literacy and to help share knowledge between different institutions and different repositories, between geographically and culturally separated societies, and between languages is a beautiful empowering thing. Here’s to more of it and entering a brave new world of linked open data. Thank you.

By way of closing I’d like to show you the video presentations the students on the Data Science for Design MSc students came up with as the final outcome of their project to import the Survey of Scottish Witchcraft database into Wikidata.

Here are two data visualisation videos they produced:

Further reading

 3 steps to better demonstrate your institution’s commitment to Open Knowledge and Open Science.

  1. Allocate time/buy out time for academics & postdoctoral researchers to add university research (backed up with citations) to Wikipedia in existing/new pages. Establishing relevance is the most important aspect of adding university research so an understanding of the subject matter is important along with ensuring the balance of edits meets the ethos of Wikipedia so that any possible suggestion of promotion/academic boosterism is outweighed by the benefit of subject experts paying knowledge forward for the common good. At least three references are required for a new article on Wikipedia so citing the work of fellow professionals goes some way to ensuring the article has a wider notability and helps pay it forward. Train contributors prior to editing to ensure they are aware of Wikipedia’s policies & guidelines and monitor their contributions to ensure edits are not reverted.
  2. Identify the most cited works by your university’s researchers which are already on Wikipedia using Altmetric software. Once identified, systematically add in the Open Access links to any existing (paywalled) citations on Wikipedia and complete the edit by adding in the OA symbol (the orange padlock) using the {{open access}} template. Also join WikiProject Open Access.
  3. Help build up a bibliographic repository of structured machine-readable (and multilingual) linked open data on both university researchers AND research papers in Wikidata using the easy-to-use suite of tools available.

Wikidata in the Classroom – Data Literacy for the next generation


The University of Edinburgh are looking to support the development of a data-literate workforce over the next ten years to support Scotland’s growing digital economy. This therefore represents a huge opportunity for educators, researchers and data scientists to support students in this aim. The first Wikidata in the Classroom assignment at the university is taking place this semester on the Data Science for Design MSc course and two groups of students are working on a project to import the Survey of Scottish Witchcraft database into Wikidata to see what possibilities surfacing this data as structured linked open data can achieve.

Wikidata in the Classroom

The New York Times described this current era as an ‘era of data but no facts’. Data is increasingly valuable as a key driver of the 21st century economy and is certainly abundant with 90% of the world’s data reportedly created in the last two years. Yet, it has never been more difficult to find ‘truth in the numbers’ with over 60 trillion pages to navigate and terabytes of unstructured data to (mis)interpret.

The way forward is clear.

  • “We need to increase the reputational consequences and change the incentives for making false statements… right now, it pays to be outrageous, but not to be truthful.”(Nyhan in the Economist, 2016)
  • ”This challenge is not just for school librarians to prepare the next generation to be informed but for all librarians to assist the whole population.”(Abram, 2016)

Issues at the heart of the information age have been exposed: there exists a glut of information & a sea of data to navigate with little formalised guidance as to how to find our way through it. For the beleaguered student, this glut makes it near impossible to find ‘truth in the numbers’. Therefore there are huge areas of convergence in developing information & data literacy in the next generation and developing Wikidata as a linked hub of verifiable data; fueling discovery and surfacing open knowledge through Google’s Knowledge Graph but, importantly, providing the digital provenance so it can be checked.

Meeting the information & data literacy needs of our students

The Edinburgh and South East Scotland City Region has recently secured a £1.1bn City Region deal from the UK and Scottish Governments. Out of this amount, the University of Edinburgh will receive in the region of £300 million towards making Edinburgh the ‘data capital of Europe’ through developing data-driven innovation. Data “has the potential to transform public and private organisations and drive developments that improve lives.” More specifically, the university is being trusted with the responsibility of delivering a data-literate workforce of 100,000 young people over the next ten years; a workforce equipped with the data skills necessary to meet the needs of Scotland’s growing digital economy.

The implementation of Wikidata in the curriculum therefore presents a massive opportunity for educators, researchers and data scientists alike; not least in honouring the university’s commitment to the creating, curating & dissemination of open knowledge. A Wikidata assignment allows students to develop their understanding of, and engagement with, issues such as: data completeness; data ethics; digital provenance; data analysis; data processing; as well as making practical use of a raft of tools and data visualisations. The fact that Wikidata is also linked open data means that students can help connect to & leverage from a variety of other datasets in multiple languages; helping to fuel discovery through exploring the direct and indirect relationships at play in this semantic web of knowledge. This real-world application of teaching and learning enables insights in a variety of disciplines; be it in open science, digital humanities, cultural heritage, open government and much more besides. Wikidata is also a community-driven project so this allows students to work collaboratively and develop the online citizenship skills necessary in today’s digital economy.

Data Science for Design MSc – Importing the Survey of Scottish Witchcraft database into Wikidata

Packed house at the Data Fair for the Data Science for Design MSc course – 26 October 2017 (Own work, CC-BY-SA)

At the University of Edinburgh, we have begun our first Wikidata in the Classroom assignment this semester on the Data Science for Design MSc course. At the course’s Data Fair on 26th October 2017, researchers from across the university presented the 45 masters students in Design Informatics with approximately 13 datasets to choose from to work on in groups of three. Happily, two groups were enthused to import the university’s Survey of Scottish Witchcraft database into Wikidata (the choice of database to propose was suggested by a colleague). This fabulous resource began life in the 1990s before being realised in 2001-2003. It had as its aim to collect, collate and record all known information about accused witches and witchcraft belief in early modern Scotland (from 1563 to 1736) in a Microsoft Access database and to create a web-based user interface for the database. Since 2003, the data has remained static in the Access database and so students at the 2018 Data Fair were invited to consider what could be done if the data were exported into Wikidata, given multilingual labels and linked to other datasets? Beyond this, what new insights & visualisations of the data could be achieved?

The methodology

A similar methodology to managing Wikipedia assignments was employed; making the transition from managing a Wikipedia assignment to managing a Wikidata assignment an easy one. The two groups of students underwent a 1.5 hour practical induction on working with Wikidata and third party applications such as Histropedia, the timeline of everything, before being introduced to the Access database. They then discussed collaboratively how best to divide the task of analysing and exporting the data before deciding one group would work on (1) importing records for the 3,212 accused witches while the other group would work on (2) the import of the witch trial records and (3) the people associated with these trials (lairds, judges, ministers, prosecutors, witnesses etc).

At this current juncture, the groups have researched and now submitted their data models for review. Now the proposed data model has been checked and agreed upon, the students are ready to process the data from the Access database into a format Wikidata can import (making use of the Wikidata plug-in on Google Spreadsheets). Once this stage is complete, the students can then choose how to visualise the linked data in a number of ways; such as maps, timelines, graphs, bubble charts and more. The students are to complete their project by presenting their insights and data visualisations in an engaging way of their choice on the 30th of November 2017.

North Berwick witches – the logo for the Survey of Scottish Witchcraft database (Public Domain, via Wikimedia Commons)

The way forward

The hope is that this project will aid the students’ understanding of data literacy through the practical application of working with a real-world dataset and help shed new light on a little understood period of Scottish history. This, in turn, may help fuel discoveries by dint of surfacing this data and linking it with other related datasets across the UK, across Europe and beyond. As the Survey of Scottish Witchcraft’s website states itself Our list of people involved in the prosecution of witchcraft suspects can now be used as the basis for further inquiry and research.“

The power of linked open data to share knowledge between different institutions, between geographically and culturally separated societies, and between languages is a beautiful thing. Here’s to many more Wikidata in the Classroom assignments.

Seeing the links at the ‘Celtic Knot’ – Wikipedia Language Conference

By David J. Fred [CC BY-SA 2.5 (http://creativecommons.org/licenses/by-sa/2.5)], via Wikimedia Commons
Tying the Celtic Knot. Pic by David J. Fred [CC BY-SA 2.5 (http://creativecommons.org/licenses/by-sa/2.5)], via Wikimedia Commons

The first ‘Celtic Knot’ – Wikipedia Language Conference will take place Thursday 6 July 2017 at the University of Edinburgh in collaboration with Wikimedia UK. This Wikimedia event will focus on Celtic Languages and Indigenous Languages, showcasing innovative approaches to open education, open knowledge and open data that support and grow language communities.

CC-BY-SA (Own work)
CC-BY-SA (Own work)

To assist with seeing the connections and areas of commonality between your work and the Celtic Knot conference please read the below guide to the Wikimedia projects:

The Celtic Knot conference is jointly supported by the University of Edinburgh and Wikimedia UK.

Wikimedia UK logo
Wikimedia UK logo

Wikimedia UK is the registered charity that supports and promotes Wikipedia and the other Wikimedia projects, and the volunteers who write, edit and curate the content of the projects.

Our mission is to help people and organisations create and preserve open knowledge and to provide easy access for all. We support the widest possible public access to, use of and contribution to open content of an encyclopaedic or educational nature.

  • Culture: We work closely with cultural institutions, including galleries, libraries, archives and museums (GLAMs) to help them realise the potential of openly-licensed content for public benefit.
  • Education: Wikipedia is more than a reference work. All over the world people and institutions are exploring the ways that Wikipedia can be used as a formal education tool. It belongs in education.
  • Volunteers: The Wikimedia projects are written, edited and curated by volunteers who are just like you. There are many ways to get involved – there are activities to suit the interests of everybody. You can also become a member of the charity.
Wikimedia's family of Open Knowledge projects
Wikimedia’s family of Open Knowledge projects


Wikimedia’s family of Open Knowledge projects include:

  • Wikipedia: the free online encyclopaedia exists in each Celtic and Indigenous language and Wikipedia’s new Content Translation tool allows articles to be translated easily between different language Wikipedias.
  • Wikimedia Commons: a media file repository making available public domain and freely-licensed educational media content (images, sound and video clips) to everyone, in their own language.
  • Wikidata is a free and open knowledge base that can be read and edited by both humans and machines. Wikidata acts as central storage for the structured data of its Wikimedia sister projects and many other sites and services beyond. Wikidata can connect other databases and collections of information, allowing computers and software to see connections between hundreds of data sources. GLAM institutions (galleries, libraries, archives and museums) realise that their collections become more useful and reusable when they are deeply interlinked with other collections around the world. Creating open structured data for their collections increases their impact on the public.
  • WikisourceThe Free Library – is a multilingual project to create a growing free content library of OCR-ed source texts, as well as translations of source texts in any language including constitutional documents, court rulings, plays, poems, songs, novels, short stories, letters, travel writing, speeches, obituaries, news articles and more.
  • Wiktionary, a collaborative project to produce a free-content multilingual dictionary.
  • Wikibooks is a multilingual project for collaboratively writing open-content textbooks that anyone can edit including textbooks, annotated texts, instructional guides, and manuals. These materials can be used in a traditional classroom, an accredited or respected institution, a home-school environment or for self-learning.
  • Wikivoyage—a multilingual, web-based project to create a free, complete, up-to-date, and reliable worldwide travel guide.

In addition, the Wiki Education Foundation connects secondary & higher education to the publishing power of Wikipedia. Bridging Wikipedia and academia creates opportunities for any learner to contribute to, and access, open knowledge. We cultivate deeper learning for students as they expand Wikipedia articles for course assignments. We work with libraries to expand the public’s access to their resources. We support academic associations as they expand and improve Wikipedia’s coverage of their field.

If you can see a clear commonality between your work and the projects above then we welcome diverse attendees and presenters working in Celtic and Indigenous languages ranging from Wikimedians, educators, researchers, information professionals, media professionals, linguists, translators, learning technologists and more coming together to share good practice and find fruitful new collaborations to support language communities as a result of the event.

Conference Themes

  • Building language confidence: participation, public engagement & social equality.
  • Putting our language on the map: preserving & opening up our cultural heritage.
  • Languages on the road to open: ongoing or new projects and initiatives in open knowledge, open education and open data.
  • The politics of language: Local, national, and international policy and practice; advocacy for funding, institutional and community support and investment
  • Hacking; making; sharing

The offical call for session proposals has now closed but email ewan.mcandrew@ed.ac.uk if you would like to attend or have a session you would like to showcase.

NB: Abstracts have now been reviewed as of April 2017 and notifications sent out to speakers.

Open Knowledge meetup at National Library of Scotland

On 19th January 2016, I attended my first ‘Open Knowledge‘ meetup at the National Library of Scotland.

Link here: Open Knowledge meetup at NLS

In an informal friendly setting, with a lovely assortment of sandwiches, nibbles and drinks I was able to observe an equally lovely assortment of Open Knowledge initiatives espoused by the evening’s speakers including:

Jeremy Darot on Edinburgh Open Data Map. Utilising lots of cool data to populate OpenStreetMap. Data like planning projects, schools, GP surgeries, shops, catchment areas, air quality, green belt areas & much more besides. Phew!

Jeremy Darot
Jeremy Darot

Also, the University of Edinburgh’s own Professor Richard Rodger outlined the MESH project (Mapping Edinburgh’s Social History): 60,000+ properties mapped accurately by physically walking past taking a note of every garden, wall and business with the ambition to create the most accurate city map in Edinburgh.

Then there was architect Akiko Kobayashi on fabulous project: open source house designs on Commons  which can be digitally fabricated & assembled easily.

Akiko Kobayashi
Akiko Kobayashi

Lastly, the National Library of Scotland’s own Fred Saunderson enthused about NLS’s Open Data Publication plan to publish 3-star open data (14 datasets in 2016, 8 more in 2017).

Fred Saunderson - NLS
Fred Saunderson – NLS

All in all, a great night of Open Knowledge initiatives. More please!