If life was one day

If the evolution of animals was one day... (600 million years)

• From 1am to 4am, most of the modern types of animals have evolved (Cambrian explosion)
• Animals get on land a bit at 3am. Early risers! It takes them until 7am to actually breath air.
• Around noon, first octopuses show up.
• Dinosaurs arrive at 3pm, and stick around until quarter to ten.
• Humans and chimpanzees split off about fifteen minutes ago, modern humans and Neanderthals lived in the last minute, and the pyramids were built around 23:59:59.2.

In that world, if that was a Sunday:

• Saturday would have started with the introduction of sexual reproduction
• Friday would have started by introducing the nucleus to the cell
• Thursday recovering from Wednesday's catastrophe
• Wednesday photosynthesis started, and lead to a lot of oxygen which killed a lot of beings just before midnight
• Tuesday bacteria show up
• Monday first forms of life show up
• Sunday morning, planet Earth forms, pretty much at the same time as the Sun.
• Our galaxy, the Milky Way, is about a week older
• The Universe is about another week older - about 22 days.

There are several things that surprised me here.

• That dinosaurs were around for such an incredibly long time. Dinosaurs were around for seven hours, and humans for a minute.
• That life started so quickly after Earth was formed, but then took so long to get to animals.
• That the Earth and the Sun started basically at the same time.

Addendum April 27: Álvaro Ortiz, a graphic designer from Madrid, turned this text into an infographic.

Architecture for a multilingual Wikipedia

I published a paper today:

"Architecture for a multilingual Wikipedia"

I have been working on this for more than half a decade, and I am very happy to have it finally published. The paper is a working paper and comments are very welcome.

Abstract:

Wikipedia’s vision is a world in which everyone can share in the sum of all knowledge. In its first two decades, this vision has been very unevenly achieved. One of the largest hindrances is the sheer number of languages Wikipedia needs to cover in order to achieve that goal. We argue that we need anew approach to tackle this problem more effectively, a multilingual Wikipedia where content can be shared between language editions. This paper proposes an architecture for a system that fulfills this goal. It separates the goal in two parts: creating and maintaining content in an abstract notation within a project called Abstract Wikipedia, and creating an infrastructure called Wikilambda that can translate this notation to natural language. Both parts are fully owned and maintained by the community, as is the integration of the results in the existing Wikipedia editions. This architecture will make more encyclopedic content available to more people in their own language, and at the same time allow more people to contribute knowledge and reach more people with their contributions, no matter what their respective language backgrounds. Additionally, Wikilambda will unlock a new type of knowledge asset people can share in through the Wikimedia projects, functions, which will vastly expand what people can do with knowledge from Wikimedia, and provide a new venue to collaborate and to engage the creativity of contributors from all around the world. These two projects will considerably expand the capabilities of the Wikimedia platform to enable every single human being to freely share in the sum of all knowledge.

• Architecture for a multilingual Wikipedia

Stanford seminar on Knowledge Graphs

My friend Vinay Chaudhri is organising a seminar on Knowledge Graphs with Naren Chittar and Michael Genesereth this semester at Stanford.

I have the honour to present in it as the opening guest lecturer, introducing what Knowledge Graphs are and what are good for.

Due to the current COVID situation, the seminar was turned virtual, and opened to everyone to attend to.

Other speakers during the semester include Juan Sequeda, Marie-Laure Mugnier, Héctor Pérez Urbina, Michael Uschold, Jure Leskovec, Luna Dong, Mark Musen, and many others.

• CS520 at Stanford, Spring 2020

Change is in the air

I'll be prophetic: the current pandemic will shine a bright light on the different social and political systems in the different countries. I expect to see noticeable differences in how disruptive the handling of the situation by the government is, how many issues will be caused by panic, and what effect freely available health care has. The US has always been on the very end of admiring the self sustained individual, and China has been on the other end of admiring the community and its power, and Europe is somewhere in the middle (I am grossly oversimplifying).

This pandemic will blow over in a year or two, it will sweep right through the US election, and the news about it might shape what we deem viable and possible in ways beyond the immediately obvious. The possible scenarios range all the way from high tech surveillance states to a much wider access to social goods such as health and education, and whatever it is, the pandemic might be a catalyst towards that.

Wired: "Wikipedia is the last best place on the Internet"

WIRED published a beautiful ode to Wikipedia, painting the history of the movement with broad strokes, aiming to capture its impact and ambition with beautiful prose. It is a long piece, but I found the writing exciting.

Here's my favorite paragraph:

"Pedantry this powerful is itself a kind of engine, and it is fueled by an enthusiasm that verges on love. Many early critiques of computer-assisted reference works feared a vital human quality would be stripped out in favor of bland fact-speak. That 1974 article in The Atlantic presaged this concern well: “Accuracy, of course, can better be won by a committee armed with computers than by a single intelligence. But while accuracy binds the trust between reader and contributor, eccentricity and elegance and surprise are the singular qualities that make learning an inviting transaction. And they are not qualities we associate with committees.” Yet Wikipedia has eccentricity, elegance, and surprise in abundance, especially in those moments when enthusiasm becomes excess and detail is rendered so finely (and pointlessly) that it becomes beautiful."

They also interviewed me and others for the piece, but the focus of the article is really on what the Wikipedia communities have achieved in our first two decades.

Two corrections: - I cannot be blamed for Wikidata alone, I blame Markus Krötzsch as well - the article says that half of the 40 million entries in Wikidata have been created by humans. I don't know if that is correct - what I said is that half of the edits are made by human contributors

• Wired: Wikipedia is the last best place on the internet"

Normbrunnenflasche

It's a pity there's no English Wikipedia article about this marvellous thing that exemplifies Germany so beautifully and quintessentially: the Normbrunnenflasche.

I was wondering the other day why in Germany sparkling water is being sold in 0.7l bottles and not in 1l or 2l or whatever, like in the US (when it's sold here at all, but that's another story).

Germany had a lot of small local producers and companies. To counter the advantages of the Coca Cola Company pressing in the German market, in 1969 a conference of representatives of the local companies decided to introduce a bottle design they all would use. This decision followed a half year competition and discussion on what this bottle should look like.

Every company would use the same bottle for sparkling water and other carbonated drinks, and so no matter which one you bought, the empty bottle would afterwards be routed to the closest participating company, not back home, therefore reducing transport costs and increasing competitiveness against Coca Cola.

The bottle is full of smart features. The 0.7l were chosen to ensure that the drink remained carbonated until the last sip, because larger bottles would last longer and thus gradually loose carbonization.

The form and the little pearls outside were chosen for improved grip, but also to symbolize the sparkles of the carbonization.

The metal screw cap was the real innovation there, useful for drinks that could increase pressure due to the carbonization.

And finally two slightly thicker bands along the lower half of the bottle that would, while being rerouted for another usage, slowly get more opaque due to mechanical pressure, thus indicating how well used the individual bottle was, so they could be taken out of service in time before breaking at the customer.

The bottles were reused an average of fifty times, their boxes an average of hundred times. More than five billion of them have been brought into circulation in the fifty years since their adoption, for an estimated quarter of a trillion fillings.

• Normbrunnenflasche on German Wikipedia

A new decade?

The job of an ontologist is to define concepts. And since I see some posts commenting on whether a decade is closing and a new decade is starting tonight, here's my private, but entirely official position.

A decade is a consecutive timespan of ten years, and therefore at every given point a new decade starts and one ends. But that's a trivial answer to the question and not very useful.

There are two ways to count calendar decades, and both are arbitrary and rely on retconning, I mean, they really on redefining the past. Therefore there is no right or wrong.

Method one is by using the proleptic Gregorian calendar, and starting with the year 1 and ending with the year 10, and calling that the first decade. If you keep counting, then the twohundredandthird decade will start on January 1st 2021, and we are currently firmly in the twohundredandsecond decade, and will stay there for another year.

Method two is based on the fact that for a millennium now and for many years to come there's a time period that conveniently lasts a decade where the years start with the same three digits. That is, the years starting with 202, which are called the 2020s, the ones with 199 which are called the 1990s (or sometimes just the 90s), etc. For centuries now we can find support for these kind of decades being widely used. According to this method, tonight marks a new decade.

So whether you are celebrating a new year tonight or not (because there are many other calendars out there too), or a new decade or not, I wish you wonderful 2020s!

SWAT4HCLS trip report

This week saw the 12th SWAT4HCLS event in Edinburgh, Scotland. It started with a day of tutorials and workshops on Monday, December 10th, on topics such as SPARQL, querying, ontology matching, and using Wikibase and Wikidata.

Conference presentations went on for two days, Tuesday and Wednesday. This included four keynotes, including mine on Wikidata, and how to move beyond Wikidata (presenting the ideas from my Abstract Wikipedia papers). The other three keynotes (as well as a number of the paper presentation) were all centered on the FAIR concept which I already saw being so prominent at the eScience conference earlier this year. FAIR as in Findable, Accessible, Interoperable, and Reusable publication of data. I am very happy to see these ideas spread out so prominently!

Birgitta König-Ries talked about how to use semantic technologies to manage FAIR data. Dov Greenbaum talked about how licenses interplay with data and what it means for FAIR data - personally, my personal favorite of the keynotes, because of my morbid fascination regarding licenses and intellectual property rights pertaining to data and knowledge. He actually confirmed my understanding of the area - that you can’t really use copyright for data, and thus the application of CC-BY or similar licenses to data would stand on shaky grounds in a court. The last keynote was by Helen Parkinson, who gave a great talk on the issues that come up when building vocabularies, including issues around over-ontologizing (and the siren call of just keeping on modeling) and others. She put the issues in parallel to the travels of Odysseus, which was delightful.

The conference talks and posters were really on spot on the topic of the conference: using semantic web technologies in the life sciences, health care, and related fields. It was a very satisfying experience to see so many applications of the technologies that Semantic Web researchers and developers have been creating over the years. My personal favorite was MetaStanza, web components that visualize SPARQL results in many different ways (a much needed update to SPARK, that Andreas Harth and I had developed almost a decade ago).

On Thursday, the conference closed with a Hackathon day, which I couldn’t attend unfortunately.

Thanks to the organizers for the event, and thanks again for the invitation to beautiful Edinburgh!

Other trip reports (send me more if you have them):

• Roderic Page

Frozen II in Korea

This is a fascinating story, that just keeps getting better (and Hollywood Reporter is only scratching the surface here, unfortunately): an NGO in South Korea is suing Disney for "monopolizing" the movie screens of the country, because Frozen II is shown on 88% of all screens.

Now, South Korea has a rich and diverse number of movie theatres - they have the large cineplexes in big cities, but in the less populated areas they have many small theatres, often with a small number of screens (I reckon it is similar to the villages in Croatia, where there was only a single screen in the theater, and most movies were shown only once, and there were only one or two screenings per day, and not on every day). The theatres are often independent, so there is no central planning about which movies are being shown (and today, it rarely matters today how many copies of a movie are being made, as many projectors are digital and thus unlimited copies can be created on the fly - instead of waiting for the one copy to travel from one town to the next, which was the case in my childhood).

So how would you ensure that these independent movies don't show a movie too often? By having a centralized way that ensures that not too many screens show the same movie? (Preferably on the Blockchain, using an auction system?) Good luck with that, and allowing the local theatres to adapt their screenings to their audiences.

But as said, it gets better: the 88% number is being arrived at by counting how many of the screens in the country showed Frozen II on a given day. It doesn't mean that that screen was used solely for Frozen II! If the screen was used at noon for a showing of Frozen II, and at 10pm for a Korean horror movie, that screen counts for both. Which makes the percentage a pretty useless number if you want to show monopolistic dominance (also, because the numbers add up to far more than 100%). Again, remember that in small towns there is often a small number of screens, and they have to show several different movies on the same screen. If the ideas of the lawsuit would be enacted, you would need to keep off Frozen II from a certain number of screens! Which basically makes it impossible to allow kids and teens in less populated areas to participate in event movie-going such as Frozen II and trying to avoid spoilers in Social Media afterwards.

Now, if you look how many screenings, instead of screens, were occupied by Frozen II, the number drops down to 46% - which is still impressive, but far less dominant and monopolistic than the 88% cited above (and in fact below the 50% the Korean law requires to establish dominance).

And even more impressive: in the end it is up to the audience. And even though 'only' 46% of the screenings were on Frozen II, every single day since its release between 60% and 85% of all revenue was going to Frozen II. So one could argue that the theatres were actually underserving the audience (but then again, that's not how it really works, because screenings are usually in rooms with hundred or more seats, and they can be very differently filled - and showing a blockbuster three times with almost full capacity, and showing a less popular movie once with only a dozen or so tickets sold might still have served the local community better than only running the block buster).

I bet the NGO's goal is just to raise awareness about the dominance of the American entertainment industry, and for that, hey, it's certainly worth a shot! But would they really want to go back to a system where small local cinemas would not be able to show blockbusters for a long time, involving a complicated centralized planning component?

(Also, I wish there was a way to sign up for updates on a story, like this lawsuit. Let me know if anyone knows of such a system!)

• Hollywood Reporter

Machine Learning and Metrology

There are many, many papers in machine learning these days. And this paper, taking a step back, and thinking about how researchers measure their results and how good a specific type of benchmarks even can be - crowdsourced golden sets. It brings a convincing example based on word similarity, using terminology and concepts from metrology, to show how many results that have been reported are actually not supported by the golden set, because the resolution of the golden set is actually insufficient. So there might be no improvement at all, and that new architecture might just be noise.

I think this paper is really worth the time of people in the research field. Written by Chris Welty, Lora Aroyo, and Praveen Paritosh.

• Metrology for AI: From Benchmarks to Instruments

The story of the Swedish calendar

Most of us are mostly aware how the calendar works. There’s twelve months in a year, each month has 30 or 31 days, and then there’s February, which usually has 28 days and sometimes, in what is called a leap year, 29. In general, years divisible by four are leap years.

This calendar was introduced by no one else then Julius Caesar, before he became busy conquering the known world and becoming the Emperor of Rome. Before that he used to have the job title “supreme bridge builder” - the bridge connecting the human world with the world of the gods. One of the responsibilities of this role was to decide how many days to add to the end of the calendar year, because the Romans noticed that their calendar was getting misaligned with the seasons, because it was simply a bit too short. So, for every year, the supreme bridge builder had to decide how many days to add to the calendar.

Since we are talking about the Roman Republic, this was unsurprisingly misused for political gain. If the supreme bridge builder liked the people in power, he might have granted a few extra weeks. If not, no extra days. Instead of ensuring that the calendar and the seasons aligned, the calendar got even more out of whack.

Julius Caesar spearheaded a reform of the calendar, and instead of letting the supreme bridge builder decide how many days to add, the reform devised rules founded in observation and mathematical rules - leading to the calendar we still have today: twelve months each year, each with 30 or 31 days, besides February, which had 28, but every four years would have 29. This is what we today call the Julian calendar. This calendar was not perfect, but pretty good.

Over the following centuries, the role of the supreme bridge builder - or, in latin, Pontifex Maximus - transferred from the Emperor of Rome to the Bishop of Rome, the Pope. And with continuing observations over centuries it was noticed that the calendar was again getting out of sync with the seasons. So it was the Pope - Gregory XIII, later called The Great - who, in his role as Pontifex Maximus, decided that the calendar should be fixed once again. The committee he set up to work on that came up with fabulous improvements, which would guarantee to keep the calendar in sync for a much longer time frame. In addition to the rules established by the Julian calendar, every hundred years we would drop a leap year. But every four hundred years, we would skip dropping the leap year (as we did in 2000, which not many people noticed). And in 1582, this calendar - called the Gregorian calendar - was introduced.

Imagine leading a committee that comes up with rules on what the whole world would need to do once every four hundred years - and mostly having these rules implemented. How would you lead and design such a committee? I find this idea mind-blowing.

Since the time of Caesar until 1582, about fifteen centuries have passed. And in this time, the calendar was getting slightly out of sync - by one day every century, skipping every fourth. In order to deal with that shift, they decided that ten calendar days need to be skipped. Following the 4th of October 1582 was the 15th of October 1582. In 1582, there was no 5th or 14th of October, nor any of the days in between, in the countries that had the Gregorian calendar adopted.

This lead to plenty of legal discussions, mostly about monthly rents and wages: is this still a full month, or should the rent or wage be paid prorated to the number of days? Should annual rents, interests, and taxes be prorated by these ten days, or not? What day of the week should the 15th of October be?

The Gregorian calendar was a marked improvement over the Julian calendar with regards to keeping the seasons in sync with the calendar. So one might think its adoption should be a no-brainer. But there was a slight complication: politics.

Now imagine that today the Pope gets out on his balcony, and declares that, starting in five years, January to November all have 30 days, and December has 35 or 36 days. How would the world react? Would they ponder the merits of the proposal, would they laugh, would they simply adopt it? Would a country such as Italy have a different public discourse about this topic than a country such as China?

In 1582, the situation was similarly difficult. Instead of pondering the benefits of the proposal, the source of the proposal and the relation to that source became the main deciding factor. Instead of adopting the idea because it is a good idea, the idea was adopted - or not - because the Pope of the Catholic Church declared it. The Papal state, the Spanish and French Kingdoms, were first to adopt it.

Queen Elizabeth wanted to adopt it in England, but the Anglican bishops were fiercely opposed to it because it was suggested by the Pope. Other Protestant and the Orthodox countries simply ignored it for centuries. And thus there was a 5th of October 1582 in England, but not in France, and that lead to a number of confusions over the following centuries.

Ever wondered why the October Revolution started November 7? There we go. There is even a story that Napoleon won an important battle (either the Battle of Austerlitz or the Battle of Ulm) because the Russian and Austrian forces coordinated badly as the Austrians were using the Gregorian and the Russians the Julian calendar. The story is false, but it makes for a great story.

Today, the International Day of the Book is on April 23 - the death date of both Miguel de Cervantes and William Shakespeare in 1616, the two giants of literature in their respective languages - with the amusing side-effect that they actually died about two weeks apart, even though they died on the same calendar day, but in different calendars.

It wasn’t until 1923 that for most purposes all countries had deprecated the Julian calendar, and for religious purposes some still follow it - which is why the Orthodox and the Amish celebrate Christmas on January 6. Starting 2101, that should shift by another day - and I would be very curious to see whether it will, or whether by then January 6th has solidified as the Christmas date.

Possibly the most confusing story about adopting the Gregorian calendar comes from Sweden. Like most protestant countries, Sweden did not initially adopt the Gregorian calendar, and was sticking with the Julian calendar, until in 1699 they decided to switch.

Now, the idea of skipping eleven or twelve days in one go did not sound appealing - remember all the chaos that occurred in the other countries for dropping these days. So in Sweden they decided that instead of dropping the days all at once, they would drop them one by one, by skipping the leap years from 1700 until 1740, when the two calendars would finally catch up.

In 1700, February 29 was skipped in Sweden. Which didn’t bring them any closer to Gregorian countries such as Spain, because they skipped the leap year in 1700 anyway. But it brought them out of alignment with Russia - by one day.

A war with Russia started (not about the calendar, but just a week before the calendars went out of sync, incidentally), and due to the war Sweden forgot to skip the leap days in 1704 and 1708 (they had other things on their mind). And as this was embarrassing, in 1711, King Charles XII of Sweden declared to abandon the plan, and added one extra day the following year to realign it back to Russia. And because 1712 was a leap year anyway, in Sweden there was not only a February 29, but also a February 30, 1712. The only legal February 30 in history so far.

It needed not only for Charles XII to die, but also for his sister (who succeeded him) and her husband (who succeeded her) in 1751, before Sweden could move beyond that embarrassing episode, and in 1752 Sweden switched from the Julian to the Gregorian calendar, by cutting February short and ending it after February 17, following that by March 1.

Somewhere on my To-Do list, I have the wish to write a book on Wikidata. How it came to be, how it works, what it means, the complications we encountered, and the ones we missed, etc. One section in this book is planned to be about calendar models. This is an early, self-contained draft of part of that section. Feedback and corrections are very welcome.

Erdös number, update

I just made an update to a post from 2006, because I learned that my Erdös number has went down from 4 to 3. I guess that's pretty much it - it is not likely I'll ever become a 2.

The Fourth Scream

Janie loved her research. It was at the intersection of so many interesting areas - genetics, linguistics, neuroscience. And the best thing about it - she could work the whole day with these adorable vervet monkeys.

One more time, she showed the video of the flying eagle to Kassandra. The MRI helmet on Kassandra’s little head measured the neuron activation, highlighting the same region on her computer screen as the other times, the same region as with the other monkeys. Kassandra let out the scream that Janie was able to understand herself by now, the scream meaning “Eagle!”, and the other monkeys behind the bars in the far end of the room, in a cage large as half the room, ran to cover in the bushes and small caves, if they were close enough. As they did every time.

That MRI helmet was a masterpiece. She could measure the activation of the neurons in unprecedented high resolution. And not only that, she could even send inferencing waves back, stimulating very fine grained regions in the monkey’s brain. The stimulation wasn’t very fast, but it was a modern miracle.

She slipped a raspberry to Kassandra, and Kassandra quickly snatched it and stuffed it in her mouth. The monkeys came from different populations from all over Southern and Eastern Africa, and yet they all understood the same three screams. Even when the baby monkeys were raised by mute parents, the baby monkeys understood the same three screams. One scream was to warn them from leopards, one scream was to warn them from snakes, and the third scream was to warn them from eagles. The screams were universally understood by everyone across the globe - by every vervet monkey, that is. A language encoded in the DNA of the species.

She called up the aggregated areas from the scream from her last few experiments. In the last five years, she was able to trace back the proteins that were responsible for the growth of these four areas, and thus the DNA encoding these calls. She could prove that these three different screams, the three different words of Vervetian, were all encoded in DNA. That was very different from human language, where every word is learned, arbitrary, and none of the words were encoded in our DNA. Some researchers believed that other parts of our language were encoded in our DNA: deep grammatical patterns, the ability to merge chunks into hierarchies of meaning when parsing sentences, or the categorical difference between hearing the syllable ba and the syllable ga. But she was the first one to provably connect three different concrete genes with three different words that an animal produces and understands.

She told the software to create an overlapping picture of the three different brain areas activated by the three screams. It was a three dimensional picture that she could turn, zoom, and slice freely, in real time. The strands of DNA were highlighted at the bottom of the screen, in the same colors as the three different areas in the brain. One gene, then a break, then the other two genes she had identified. Leopard, snake, eagle.

She started to turn the visualization of the brain areas, as Kassandra started squealing in pain. Her hand was stuck between the cage bars and the plate with raspberries. The little thief was trying to sneak out a raspberry or two! Janie laughed, and helped the monkey get the hand unstuck. Kassandra yanked it back into the cage, looked at Janie accusingly, knowing that the pain was Janie’s fault for not giving her enough raspberries. Janie snickered, took out another raspberry and gave it to the monkey. She snatched it out of Janie’s hand, without stopping the accusing stare, and Janie then put the plate to the other side of the table, in safe distance and out of sight of Kassandra.

She looked back at the screen. When Kassandra cried out, her hand had twitched, and turned the visualization to a weird angle. She just wanted to turn it back to a more common view, when she suddenly stopped.

From this angle, she could see the three different areas, connecting together with the audiovisual cortex at a common point, like the leaves of a clover. But that was just it. It really looked like three leaves of a four-leaf clover. The area where the fourth leaf would be - it looked a lot like the areas where the other three leaves were.

She zoomed into the audiovisual cortex. She marked the neurons that triggered each of the three leaves. And then she looked at the fourth leaf. The connection to the cortex was similar. A bit different, but similar enough. She was able to identify what probably are the trigger-neurons, just like she was able to find them for the other three areas.

She targeted the MRI helmet on the neurons connected to the eagle trigger neurons, and with a click she sent a stimulus. Kassandra looked up, a bit confused. Janie looked at the neurons, how they triggered, unrolled the activation patterns, and saw how the signal was suppressed. She reprogrammed the MRI helmet, refined the neurons to be stimulated, and sent off another stimulus.

Kassandra yanked her head up, looking around, surprised. She looked at her screen, but it showed nothing as well. She walked nervously around inside the little cage, looking worriedly to the ceiling of the lab, confused. Janie again analyzed the activation patterns, and saw how it almost went through. There seemed to be a single last gatekeeper to pass. She reprogrammed the stimulator again. Third time's the charm, they say. She just remembered a former boyfriend, who was going on and on about this proverb. How no one knew how old it was, where it began, and how many different cultures all over the world associate trying something three times with eventual success, or an eventual curse. How some people believed you need to call the devil's name three times to —

Kassandra screamed out the same scream as before, the scream saying “Eagle!”. The MRI helmet had sent the stimulus, and it worked. The other monkeys jumped for cover. Kassandra raised her own arms above her head, peeking through her fingers to find the eagle she had just sensed.

Janie was more than excited! This alone will make a great paper. She could get the monkeys to scream out one of the three words of their language by a simple stimulation of particular neurons! Sure, she expected this to work - why wouldn’t it? But the actual scream, the confirmation, was exhilarating. As expected, the neurons now had a heightened potential, were easier to activate, waiting for more input. They slowly cooled down as Kassandra didn’t see any eagles.

She looked at the neurons connected to the fourth leaf. The gap. Was there a secret, fourth word hidden? One that all the zoologists studying vervet monkeys have missed so far? What would that word be? She reprogrammed the MRI helmet, aiming at the neurons that would trigger the fourth leaf. If her theory was right. With another click she sent a stimulus to the —

Janie was crouching in the corner of the room, breathing heavily, cold sweat was covering her arms, her face, her whole body. Her clothes were clamp. Her arms were slung above her head. She didn’t remember how she got here. The office chair she was just sitting in a moment ago, laid on the floor. The monkeys were quiet. Eerily quiet. She couldn’t see them from where she was, she couldn’t even see Kassandra from here, who was in the cage next to her computer. One of the halogen lamps in the ceiling was flickering. It wasn’t doing that before, was it?

She slowly stood up. Her body was shivering. She felt dizzy. She almost stumbled, just standing up. She slowly lowered her arms, but her arms were shaking. She looked for Kassandra. Kassandra was completely quiet, rolled up in the very corner of her cage, her arms slung around herself, her eyes staring catatonically forward, into nothing.

Janie took a step towards the middle of the room. She could see a bit more of the cage. The monkeys were partly huddled together, shaking in fear. One of them laid in the middle of the cage, his face in a grimace of terror. He was dead. She thought it was Rambo, but she wasn’t sure. She stumbled to the computer, pulled the chair from the floor, slumped into it.

The MRI helmet had recorded the activation pattern. She stepped through it. It did behave partially the same: the neurons triggered the unknown leaf, as expected, and that lead to activate the muscles around the lungs, the throat, the tongue, the mouth - in short, that activated the scream. But, unlike with the eagle scream, the activation potential did not increase, it was now suppressed. Like if it was trying to avoid a second triggering. She checked the pattern: yes, the neuron triggered that suppression itself. That was different. How did this secret scream sound?

Oh no! No, no, no, no, NOO!! She had not recorded the experiment. How stupid!

She was excited. She was scared, too, but she tried to push that away. She needed to record that scream. She needed to record the fourth word, the secret word of vervet monkeys. She switched on all three cameras in the lab, one pointed at the large cage with the monkeys, the other two pointing at Kassandra - and then she changed her mind, and turned one onto herself. What has happened to herself? Why couldn’t she remember hearing the scream? Why was she been crouching on the floor like one of the monkeys?

She checked her computer. The MRI helmet was calibrated as before, pointing at the group of triggering neurons. The suppression was ebbing down, but not as fast as she wanted. She increased the stimulation power. She shouldn’t. She should follow protocol. But this all was crazy. This was a cover story for Nature. With her as first author. She checked the recording devices. All three were on. The streams were feeding back into her computer. She clicked to send the sti—

She felt the floor beneath her. It was dirty and cold. She was laying on the floor, face down. Her ears were ringing. She turned her head, opened her eyes. Her vision was blurred. Over the ringing in her ears she didn’t hear a single sound from the monkeys. She tried to move, and she felt her pants were wet. She tried to stand up, to push herself up.

She couldn’t.

She panicked. Shivered. And when she felt the tears running over her face, she clenched her teeth together. She tried to breath, consciously, to collect herself, to gain control. Again she tried to stand up, and this time her arms and legs moved. Slower than she wanted. Weaker than she hoped. She was shaking. But she moved. She grabbed the chair. Pulled herself up a bit. The computer screen was as before, as if nothing has happened. She looked to Kassandra.

Kassandra was dead. Her eyes were bloodshot. Her face was a mask of pure terror, staring at nothing in the middle of the room. Janie tried to look at the cage with the other monkeys, but she couldn’t focus her gaze. She tried to yank herself into the chair.

The chair rolled away, and she crashed to the floor.

She had went too far. She had made a mistake. She should have had followed protocol. She was too ambitious, her curiosity and her impatience took the best of her. She had to focus. She had to fix things. But first she needed to call for help. She crawled to the chair. She pulled herself up, tried to sit in the chair, and she did it. She was sitting. Success.

Slowly, she rolled back to the computer. Her office didn’t have a phone. She double-clicked on the security app on her desktop. She had no idea how it worked, she never had to call security before. She hoped it would just work. A screen opened, asking her for some input. She couldn’t read it. She tried to focus. She didn’t know what to do. After a few moments the app changed, and it said in big letters: HELP IS ON THE WAY. STAY CALM. She closed her eyes. Breathed. Good.

After a few moments she felt better. She opened her eyes. HELP IS ON THE WAY. STAY CALM. She read it, once, twice. She nodded, her gaze jumping over the rest of the screen.

The recording was still on.

She moved the mouse cursor to the recording app. She wanted to see what has happened. There was nothing to do anyway, until security came. She clicked on the play button.

The recording filled three windows, one for each of the cameras. One pointed at the large cage with the vervet monkeys, two at Kassandra. Then, one of the cameras pointing at Kassandra was moved, pointing at Janie, just moments ago - it was moments, was it? - sitting at the desk. She saw herself getting ready to send the second stimulus to Kassandra, to make her call the secret scream a second time.

And then, from the recording, Kassandra called for a third time.

The end

History of knowledge graphs

An overview on the history of ideas leading to knowledge graphs, with plenty of references. Useful for anyone who wants to understand the background of the field, and probably the best current such overview.

• History of knowledge graphs

On the competence of conspiracists

“Look, I’ll be honest, if living in the US for the last five years has taught me anything is that any government assemblage large enough to try to control a big chunk of the human population would in no way be consistently competent enough to actually cover it up. Like, we would have found out in three months and it wouldn’t even have been because of some investigative reporter, it would have been because one of the lizards forgot to put on their human suit on day and accidentally went out to shop for a pint of milk and like, got caught in a tik-tok video.” -- Os Keyes, WikidataCon, Keynote "Questioning Wikidata"

Power in California

It is wonderful to live in the Bay Area, where the future is being invented.

Sure, we might not have a reliable power supply, but hey, we have an app that connects people with dogs who don't want to pick up their poop with people who are desperate enough to do this shit.

Another example how the capitalism that we currently live failed massively: last year, PG&E was found responsible for killing people and destroying a whole city. Now they really want to play it safe, and switch off the power for millions of people. And they say this will go on for a decade. So in 2029 when we're supposed to have AIs, self-driving cars, and self-tieing Nikes, there will be cities in California that will get their power shut off for days when there is a hot wind for an afternoon.

Why? Because the money that should have gone into, that was already earmarked for, making the power infrastructure more resilient and safe went into bonus payments for executives (that sounds so cliché!). They tried to externalize the cost of an aging power infrastructure - the cost being literally the life and homes of people. And when told not to, they put millions of people in the dark.

This is so awfully on the nose that there is no need for metaphors.

San Francisco offered to buy the local power grid, to put it into public hands. But PG&E refused that offer of several billion dollars.

So if you live in an area that has a well working power infrastructure, appreciate it.

• NPR on the blackouts

Academic lineage

Sorry for showing off, but it is just too cool not to: here is a visualization of my academic lineage according to Wikidata.

Query: w.wiki/AE8

Bring me to your leader!

"Bring me to your leader!", the explorer demanded.

"What's a leader?", the natives asked.

"The guy who tells everyone what to do.", he explained with some consternation.

"Oh yeah, we have one like that, but why would you want to talk to him? He's unbearable."

AKTS 2019

September 24 was the AKTS workshop - Advanced Knowledge Technologies for Science in a FAIR world - co-located with the eScience and Gateways conferences in San Diego. As usual with my trip reports, I won't write about every single talk, but offer only my own personal selection and view. This is not an official report on the workshop.

I had the honor of kicking off the day. I made the proposal of using Wikidata for describing datasets so that dataset catalogs can add these descriptions to their indexes. The standard way to do so is to use Schema.org annotations describing the datasets, but our idea here was to provide a fallback solution in case Schema.org cannot be applied for one reason or the other. Since the following talks would also be talking about Wikidata I used the talk to introduce Wikidata in a bit more depth. In parallel, I kicked the same conversation off on Wikidata as well. The idea was well received, but one good question was raised by Andrew Su: why not add Schema.org annotations to Wikidata instead?

After that, Daniel Garijo of USC's ISI presented WDPlus, Wikidata Plus, which presented a prototype for how to extend Wikidata with more data (particularly tabular data) from external data sources, such as censuses and statistical publications. The idea is to surround Wikidata with a layer of so-called satellites, which materialize statistical and other external data into Wikidata's schema. They implemented a mapping languages, T2WDML, that allows to grab CSV numbers and turn them into triples that are compatible with Wikidata's schema, and thus can be queried together. There seems to be huge potential in this idea, particularly if one can connect the idea of federated SPARQL querying with on-the-fly mappings, extending Wikidata to a virtual knowledge base that would be easily several times its current size.

Andrew Su from Scripps Research talked about using Wikidata as a knowledge graph in a FAIR world. He presented their brilliant Gene Wiki project, about adding knowledge about genes and proteins to Wikidata. He presented the idea of using Wikidata as a generalized back-end for customized frontend-applications - which is perfect. Wikidata's frontend is solid and functional, but in many domains there is a large potential to improve the UX for users in specific domains (and we are seeing some if flowering more around Lexemes, with Lucas Werkmeister's work on lexical forms). Su and his lab developed ChlamBase which allows the Chlamydia research community to look at the data they are interested in, and to easily add missing data. Another huge advantage of using Wikidata? Your data is going to live beyond the life of the grant. A great overview of the relevant data in Wikidata can be seen in this rich and huge and complex diagram.

The talks switched more to FAIR principles, first by Jeffrey Grethe of UCSD and then Mark Musen of Stanford. Mark was pointing out how quickly FAIR turned from a new idea to a meme that was pervasive everywhere, and the funding agencies now starting to require it. But data often has issues. One example: BioSample is the best metadata NIH has to offer. But 73% of the Boolean metadata values are not 'true' or 'false' but have values like "nonsmoker" or "recently quitted". 26% of the integers were not parseable. 68% of the entries from a controlled vocabulary were not. Having UX that helped with entering this data would be improving the quality considerably, such as CEDAR.

Carole Goble then talked about moving towards using Schema.org for FAIRer Life Sciences resources and defining a Schema.org profile that make datasets easier to use. The challenges in the field have been mostly social - there was a lot of confidence that we know how to solve the technical issues, but the social ones provide to be challenging. Carol named four of those explicitly:

1. ontology-itis
2. building consensus (it's harder than you think)
3. the Schema.org Catch-22 (Schema.org won't take it if there is no usage, but people won't use it until it is in Schema.org)
4. dedicated resources (people think you can do the social stuff in your spare time, but you can't)

Natasha Noy gave the keynote, talking about Google Dataset Search. The lessons learned from building it:

1. Build an ecosystem first, be technically light-weight (a great lesson which was also true for Wikipedia and Wikidata)
2. Use open, non-proprietary, standard solutions, don't ask people to build it just for Google (so in this case, use Schema.org for describing datasets)
3. bootstrapping requires influencers (i.e. important players in the field, that need explicit outreach) and incentives (to increase numbers)
4. semantics and the KG are critical ingredients (for quality assurance, to get the data in quickly, etc.)

At the same time, Natasha also reiterated one of Mark's points: no matter how simple the system is, people will get it wrong. The number of ways a date field can be written wrong is astounding. And often it is easier to make the ingester more accepting than try to get people to correct their metadata.

Chris Gorgolewski followed with a session on increasing findability for datasets, basically a session on SEO for dataset search: add generic descriptions, because people who need to find your dataset probably don't know your dataset and the exact terms (or they would already use it). Ensure people coming to your landing site have a pleasant experience. And the description is markup, so you can even use images.

I particularly enjoyed a trio of paper presentations by Daniel Garijo, Maria Stoica, Basel Shbita and Binh Vu. Daniel spoke about OntoSoft, an ontology to describe software workflows in sufficient detail to allow executing them, and also to create input and output definitions, describe the execution environment, etc. Close to those in- and output definition we find Maria's work on an ontology of variables. Maria presented a lot of work to identify the meaning of variables, based on linguistic, semantic, and ontological reasoning. Basel and Binh talked about understanding data catalogs deepers, being able to go deeper into the tables and understand the actual content in them. If one would connect the results of these three papers, one could potentially see how data from published tables and datasets could become alive and answer questions almost out of the box: extracting knowledge from tables, understanding their roles with regards to the input variables, and how to execute the scientific workflows.

Sure, science fiction, and the question is how well would each of the methods work, and how well would they work in concert, but hey, it's a workshop. It's meant for crazy ideas.

Ibrahim Burak Ozyurt presented an approach towards question answering in the bio-domain using Deep Learning, including Glove and BERT and all the other state of the art work. And it's all on Github! Go try it out.

The day closed with a panel with Mark Musen, Natasha Noy, and me, moderated by Yolanda Gil, discussing what we learned today. It quickly centered on the question how to ensure that people publishing datasets get appropriate credit. For most researchers, and particularly for universities, paper publications and impact factors are the main metric to evaluate researchers. So how do we ensure that people creating datasets (and I might add, tools, workflows, and social consensus) receive the fair share of credit?

Thanks to Yolanda Gil and Andrew Su for organizing the workshop! It was an exhausting, but lovely experience, and it is great to see the interest in this field.

Illuminati and Wikibase

When I was a teenager I was far too much fascinated by the Illuminati. Much less about the actual historical order, and more about the memetic complex, the trilogy by Shea and Wilson, the card game by Steve Jackson, the secret society and esoteric knowledge, the Templar Story, Holy Blood of Jesus, the rule of 5, the secret of 23, all the literature and offsprings, etc etc...

Eventually I went to actual order meetings of the Rosicrucians, and learned about some of their "secret" teachings, and also read Eco's Foucault's Pendulum. That, and access to the Web and eventually Wikipedia, helped to "cure" me from this stuff: Wikipedia allowed me to put a lot of the bits and pieces into context, and the (fascinating) stories that people like Shea & Wilson or von Däniken or Baigent, Leigh & Lincoln tell, start falling apart. Eco's novel, by deconstructing the idea, helps to overcome it.

He probably doesn't remember it anymore, but it was Thomas Römer who, many years ago, told me that the trick of these authors is to tell ten implausible, but verifiable facts, and tie them together with one highly plausible, but made-up fact. The appeal of their stories is that all of it seems to check out (because back then it was hard to fact check stuff, so you would use your time to check the most implausible stuff).

I still understand the allure of these stories, and love to indulge in them from time to time. But it was the Web, and it was learning about knowledge representation, that clarified the view on the underlying facts, and when I tried to apply the methods I was learning to it, it fell apart quickly.

So it is rather fascinating to see that one of the largest and earliest applications of Wikibase, the software we developed for Wikidata, turned out to be actual bona fide historians (not the conspiracy theorists) using it to work on the Illuminati, to catalog the letters they sent to reach other, to visualize the flow of information through the order, etc. Thanks to Olaf Simons for heading this project, and for this write up of their current state.

It's amusing to see things go round and round and realize that, indeed, everything is connected.