Yesterday I had the honour and pleasure to give one of the keynote speeches at the 1st workshop of Semantic AI, co-located with SEMANTiCS2022 in Vienna. I my talk “Knowledge Graphs for impactful Data Science In the Digital Humanities and IOT domain“, I talked about challenges and lessons learned in various projects where 1) Knowledge Graphs 2) Machine Learning and 3) User Contexts interact in interesting ways. The slides for my talk can be found below.
I am happy and proud I to announce that I will join Marieke van Erp and Laura Hollink as co-director of the Cultural AI lab. The lab brings together researchers from various research institutes and heritage organizations to investigate both how AI can be used to address various humanities and heritage challenges but also how we can use methods, theories and insights from the cultural domain to make better, fairer, more inclusive and diverse AI.
I am very excited about this and look forward to the wonderful research collaborations!
In the latest edition of the trade publication E-Data & Research, a nice article (in Dutch) about our research on knowledge graphs for maritime history is published. Thanks to Mathilde Jansen and of course my collaborators Stijn Schouten and Marieke van Erp! The image below shows the print article, the article can be found online here.
Our abstract “Using the SAREF ontology for interoperability and machine learning in a Smart Home environment” was accepted for a presentation at the ICT Open conference in 6-7 April 2022 in Amsterdam. In the abstract, we outline the current and future research VU and TNO are conducting in the context of the InterConnect project, specifically around the construction of IOT knowledge graphs, machine learning and rule-based applications. We look forward to presenting it in April.
[This post is the text of a 1-minute pitch at the IWDS symposium for our poster “A Polyvocal and Contextualised Semantic Web” which was published as the paper”Erp, Marieke van, and Victor de Boer. “A Polyvocal and Contextualised Semantic Web.” European Semantic Web Conference. Springer, Cham, 2021.”]
Knowledge graphs are a popular way of representing and sharing data, information and knowledge in many domains on the Semantic Web. These knowledge graphs however often represent singular -biased- views on the word, this can lead to unwanted bias in AI using this data. We therefore identify a need a more polyvocal Semantic Web.
So. How do we get there?
- We need perspective-aware methods for identifying existing polyvocality in datasets and for acquiring it from text or users.
- We need datamodels and patterns to represent polyvocal data information and knowledge.
- We need visualisations and tools to make the polyvocal knowledge accessible and usable for a wide variety of users, including domain experts or laypersons with varying backgrounds.
In the Cultural AI Lab, we investigate these challenges in several interrelated research projects, but we cannot do it, and should not do it alone and are looking for more voices to join us!
Last week, I was invited to give a guest lecture at the University of Development Studies in Tamale, Ghana. Vrije Universiteit has a very interesting and fruitful collaboration with this great university. In my presentation “Knowledge Graphs for Social Good”, I introduce the principles and practice of knowledge graphs and their role with AI. I also talked about how knowledge graphs can be (and are) used for social impact. Finally, I talk about four challenges we encountered in our own efforts to make knowledge graphs meaningful for rural users in the Global South.
We expect the recording to be shared, for now, the slides are embedded below and can be downloaded from Google Slides.
For several courses, I made a set of video lectures around Linked Data principles and practice, specifically in the context of Digital Humanities.
This contains videos showing
- the principles of Linked Data
- The RDF-Turtle syntax
- Making RDF using OntoRefine
- The hands-on exercises with Dutch Ships and Sailors
Also, this includes a sub-tutorial on using GraphDB, OntoRefine and SPARQL to
- Download and install GraphDB
- Get some interesting data in CSV
- Convert to triples using OntoRefine
- Find potential links in DBPedia
- Link your data using SPARQL -> import data
- Try out interesting SPARQL queries
This year, we organized the SEMANTiCS2021 conference in Amsterdam. Due to the ongoing COVID-19 retrictions, we opted for a hybrid conference. And hybrid it was! With 200 onsite and 264 online tickets sold this was as much a mix between online and onsite as it was a mix between industry and academia. The research track consisted of 19 papers, and the industry track was made up of 24 presentations. With four wonderful keynote speakers, a poster session and various special tracks and workshops, this was quite a full programme!
As far as I am concerned, a true success! See my Twitter-generate impression below.
[This post presents research done by Daan Raven in the context of his Master Project Information Sciences]
There is a long tradition in the Cultural Heritage domain of using structured, machine-interoperable knowledge using semantic methods and tools. However, research into developing and using ontologies specific to works of art of individual artists is persistently lacking. Such knowledge graphs would improve access to heritage information by making reasoning and inferencing possible. In his research, Daan Raven developed and applied a re-usable method, building on the ‘Methontology’ method for ontology development. We describe the steps of specification, conceptualization, integration, implementation and evaluation in a case study concerning ceramic-glass sculptor Barbara Nanning.
This work was presented at Digital Humanities Benelux 2021. The abstract and presentation as well as other digital resources related to the project can be found below:
- DHBenelux abstract (pdf)
- DHBenelux presentation (pdf)
- Knowledge Graph on Github (~15K triples)
- SPARQL endpoint: https://semanticweb.cs.vu.nl/test/sparql
Below are some examples of competency questions with pointers to SPARQL queries in YASGUI.
|Which artworks in the Verre Églomisé collection of Nanning are currently stored in her private collection?||https://api.triplydb.com/s/wKZG4UFq5|
|Show me a timeline of all process that require the use of an Annealing Kiln||https://api.triplydb.com/s/j4Qk0tHzK|
| # Show me all process steps that require the use of an annealing kiln and that have a landing page||https://api.triplydb.com/s/N5mo4uTM3|
|Show me (in Gallery) all objects made by “Jiří Pačinek Glass Lindava” (person in Wikidata)||https://api.triplydb.com/s/C6LsEgiZF|
|Show me (in Geo) the locations of creation steps for various works (uses geonames)||https://api.triplydb.com/s/THTkhOYjd|
As supervisor of many MSc and BSc theses, I find myself giving writing tips and guidelines quite often. Inspired by Jan van Gemert’s guidelines, I compiled my own document with tips and guidelines for writing an CS/AI/IS bachelor or master thesis. These are things that I personally care about and other lecturers might have different ideas. Also, this is by no means a complete list and I will use it as a living document. You can find it here: https://tinyurl.com/victorthesiswriting