The importance of Revenue Strategy for the Wikimedia Foundation lies in two main factors: the uncertain future facing us, which might endanger existing revenue sources, and the impetus to grow, mandated by the ambitions of the Wikimedia movement. The following is a summary of my reflection on Revenue Strategy for the Foundation’s Advancement department.
Challenges to the banner fundraising model
Since the creation of the Wikimedia Foundation, most of its revenue has been raised through fundraising banners: a small portion of readers of Wikipedia are prompted by banners to donate a small amount to support the continued existence of the site.
In recent years, a few trends have emerged in internet usage and challenged the banner model. The increasing use of mobile devices has translated into fewer donations compared to desktop, only compensated by improvements and optimization of banner effectiveness, as well as the growth of our email program to past donors. A stagnation in overall readership has also threatened the banner model, with internet users accessing content from Wikipedia through intermediaries and not visiting Wikipedia directly.
The Foundation’s email fundraising program is one of the existing efforts undertaken to address those challenges. Banners are the main point of entry for first-time donors; once they have donated, they can be solicited for support over email in later fundraising campaigns. Initial work in recurring donations also aims to reduce the friction of donating and build sustainability. Cultivating major donors through event and direct outreach is another way to bring in larger donations that don’t rely on direct interaction with the website.
Building on those initiatives is the first step towards longer-term financial sustainability, but it won’t be enough. As knowledge becomes more granular, remixed by others, and served through interfaces out of our control, it will become increasingly difficult to maintain a direct line of communication with people willing to support our mission. The whole concept of “readers” might become obsolete, and banner fundraising might not prove to remain a major source of revenue by 2030.
Thinking about long-term revenue strategy in this context requires thinking about strategy in broader terms, and in particular identifying our unique strengths, both today and tomorrow.
The scenarios for 2031 explore possible futures for the human ecosystem and Wikimedia’s place in it. Without purposeful, drastic change, the outlook is bleak: deep adaptation is necessary, based on our differentiators of today and tomorrow. The Wikimedia societies and brand offer a path through the possible stormy futures ahead, if we are bold enough to change.
Today, Wikipedia is mainly seen as a website: one of the top-ten websites in the world, containing millions of encyclopedia articles that are mostly considered trustworthy. However, none of those characteristics can be relied upon as stable, unique strengths.
Wikipedia is a popular website. But that popularity has grown primarily out of its ranking in search engines; as search interfaces get more clever, they have an incentive to provide immediate answers that make use of Wikipedia content but don’t actually send their users to Wikipedia.
Wikipedia is one of the most famous encyclopedias. But it is not the only one; the mere concept of the long-form, Enlightenment-style encyclopedia is even becoming obsolete as online usage and populations evolve.
Wikipedia is a source of reliable content. To date, content has been the cornerstone of our relationship with the rest of the knowledge ecosystem. Other actors, whether partners, allies, or foes, are primarily interested in using, expanding, protecting, or influencing Wikipedia’s content. But content is already no longer a unique strength of Wikipedia: for one thing, its free license not only allows, but encourages its use in a variety of contexts and interfaces. For another, technological progress leans towards a decreasing reliance on Wikipedia’s humans to generate and curate knowledge.
We can’t rely on Wikipedia’s position as a popular website, as a famous encyclopedia, or as a source of reliable content. What are our sustainable unique strengths, then?
One current differentiator is Wikimedia societies. While there are many online communities, those comprising the Wikimedia movement have a unique affinity and talent for collecting and curating free, reliable knowledge. Over the past 18 years, they have developed policies, processes, and social structures that are largely responsible for the reputation of Wikipedia. The uniqueness of Wikimedia communities resides in the culture and institutions that define them as societies, independent of the websites they work on and artifacts they produce.
Another current differentiator is the Wikipedia brand. Beyond just a name, the brand encompasses a complex set of components that define our relationship to the public. The brand includes the trust established through the hard work and integrity of Wikimedia contributors. The brand includes the love that donors express when they support us. The brand includes the principles that we have stood up for and we demonstrate every day.
Both the communities and the brand are likely to become stronger differentiators in the future. In a world swimming in data and overwhelmed with information, discernment and sensemaking are paramount. To use Hal Varian’s vocabulary, data and information are increasingly abundant inputs; trust and human judgment on information (determining what is accurate and important) are a scarce and therefore valuable complement to those inputs. It is where the Wikimedia movement brings unique value, and the brand is the vehicle of that value.
Building our future on the foundations of communities and brand helps us explore a future where Wikimedia societies may become the world’s foremost sensemaking engine. Where machines and algorithms may collect and assemble facts, but where Wikipedians organize, weigh, and nuance them. Where information may be omnipresent, but the Wikipedia brand is a sought-after indicator of trust, regardless of the medium or interface.
Implications for Revenue strategy
Elements of a revenue strategy for the Wikimedia Foundation have emerged organically. Some are evident: continuing to refine and improve the effectiveness of banner fundraising for as long as possible; continuing to develop email fundraising and major giving as complementary sources of donations that might one day overtake banner fundraising; encouraging recurring and seamless donation processes that reduce friction and increase predictability.
Another element of revenue strategy is to take a longer view, and build on today’s financial stability to plan for tomorrow. This includes a model of engagement with donors that takes into account the various stages of their life and interactions with Wikipedia. It includes investing today in a solid planned giving program that will only benefit us in several decades. It includes building out the Wikimedia Endowment today to mitigate uncertainties in future revenue, and provide the resources for experimentation as we transition to other funding models.
Those new funding models might not look like what we have become familiar with. The fully donative model doesn’t appear sufficient for long-term sustainability. Exploring revenue beyond donations means experimenting with models like fee-for-service, joint for-profit ventures, and other “earned income” options that must be allowed to take risks and fail, so long as we learn from them. Profitability and ease of launch must not be the only criteria: new ventures must also align with the larger mission and strengthen the brand, sustainability, and relevance in our ecosystem.
The last element of revenue strategy is one that goes beyond the Wikimedia Foundation. Increasing revenue to the level required by the strategic direction will require the whole movement to commit to its funding, taking advantage of its global reach and local presence. The Movement strategy working group on Revenue Streams is expected to offer recommendations for revenue strategy on a global scale.
All those elements combine to form a revenue strategy that is inextricably intertwined with the larger decisions we have to make as an organization and a movement. Even if revenue could flourish alongside a failing product, which it likely can’t, it wouldn’t be enough: money can’t buy readers. Money can’t buy relevance. Money can’t buy trust. At least not in the long run.
How much revenue we can access to fulfill our mission will depend on the story we can tell about who we are and who we have become. It can be the story of a once-popular website whose struggle to adapt became a struggle to survive. The story of knowledge communities whose decreasing relevance didn’t provide a continued incentive for public support. The story of a brand that slowly faded from the public’s memory. The story of a social movement starved of the resources it needed to advance.
Or it can be the story of a community that evolved to adapt to the world around it, and built on its unique strengths. The story of a society of trusted sensemakers that provides such value to the public and partners that it is in their vital interest to support it. The story of a brand that the public trusts, loves, and supports wherever they encounter it. The story of a vibrant social movement with the financial might to match its ambitious vision.
There are many elements of the story that we can’t control. The question is what we do with those we can. The story of our survival tomorrow is the story we choose to write today.
Knowledge has real consequences on human lives, both for individuals and for societies. As I reckoned with the privilege of growing up surrounded by books, I deepened my understanding of knowledge and the real power it holds, both as an instrument of liberation, and as a vital component of our collective survival.
The privilege of knowledge
It is easy to take knowledge for granted when you grow up surrounded by it, and have immediate access to readily-available, trustworthy information at your fingertips.
My childhood home was filled with books, and my mom even opened a volunteer-run library in our small village. I had access to education, and a fifteen-volume encyclopedia at home that I would browse at random. I would collect magazines and create little dossiers on topics of interest, putting together endearing reports for no other reason than finding it fun.
When I started editing Wikipedia, it was mostly out of curiosity and fascination. Curiosity about an encyclopedia that anyone could edit, and about the strange people who would devote their time to sharing knowledge for free. Fascination about an opportunity to record the sum of all knowledge, which appealed to my knowledge-hoarder mind. I had found my people.
But thinking of knowledge as only an abstract concept is a privilege. Thinking of Wikipedia as merely a hobby for people with too much time on their hands ignores the opportunity it represents for people who did not have the opportunity to grow up surrounded by books.
Lifelong learning & opportunity
Knowledge is a manifestation of power: withheld, it reinforces control and prevents change; liberated, it erodes structures of oppression and opens up opportunities.
Today, learning, and therefore, quality of life, are very much a matter of privilege. Your age, geography, gender, and wealth determine your level of access to quality education, if any. Affordable formal education, only available to a few, is neither inclusive nor scalable to all who need it.
Elites and other gatekeepers of knowledge in positions of power have a vested interest in preserving the status quo, whether that takes the form of denying education to girls, imprisoning journalists, or censoring the internet.
Fencing knowledge in causes a structural hoarding of opportunities: opportunities for self-determination, for better work, for healthier lives, and for toppling the self-reinforcing systems of durable inequality and exploitation.
Tomorrow, the challenges may look different, but the underlying structures of power are poised to perpetuate. The accelerated pace of industrial and technological change is rendering obsolete not just the concept of the decades-long career, but also the paradigm of retraining for career change: the skills acquired by those in the most precarious work situations become outdated before they can lead to individual prosperity.
Denied lifelong learning opportunities, many are being forced into the modern serfdom of the “gig economy.” Millions will be displaced as they see their jobs being automated and replaced by machines, which will cause mass unemployment and further concentrate wealth and power. Millions more will die as they are deprived of life-saving knowledge, while others barely survive, deprived of the means and opportunity to lift themselves out of poverty.
Knowledge can change a life. It can be an instrument of equity, and help the arc of history bend towards justice. It can be an instrument of liberation and self-empowerment for people who have been left out. But knowledge can do none of those things if it stays in the hands of the few.
Disinformation & solving problems together
Democracy relies on an informed society; oppressive regimes and fascism thrive on a disinformed one. But it is no less than the survival of humanity that is at stake if we cannot learn to tackle crises together.
Today, too many lives, particularly of infants and women, are still lost to the lack of access to trustworthy information. Disinformation goes even further: it consists of coordinated and relentless campaigns by bad actors, unscrupulous companies, and oppressive regimes, acting in the pursuit of ideology, profit, and power, against the interest of humankind.
Every day brings ample evidence of the consequences of disinformation. Doctored videos cause lynchings. Corruption and egregious partisanship cause climate change denial. Fake news cause stolen elections. Vaccines don’t cause autism, but ignorance spreads measles.
The issue is not just that of private interests mortgaging the future, spreading disinformation to cover their unsustainable extraction of resources and destruction of the planet. It is also that of the newer actors of surveillance capitalism: algorithms designed for “engagement,” short-term profit, and shareholder satisfaction are abused by bad actors to pervert democracy. Unaccountable giants position themselves as helpful assistants in navigating the flood of information deluged onto us, all the while denying their own responsibility in epidemics of viral disinformation.
Tomorrow, the challenges facing humankind will be even greater, as will the temptation to fear and blame each other for them. The climate emergency does not just bring extreme weather; it is also the harbinger of famine, plague, conflict, unbreathable air, loss of land, death of oceans, economic collapse, and mass displacement of climate refugees.
Historically exploited and disenfranchised people are, as always, the most vulnerable. Not only to disasters and other deadly consequences of status and geography, but also to fear and blame: we fear what we do not know, and we cannot understand those whose stories we have erased.
The inevitability of global heating requires deep adaptation; it will take many ingenious minds to solve those seemingly intractable conundrums. Without mutual understanding and empathy, there can be no trust. Without widespread knowledge of the issues confronting us, there can be no awareness, no agreement, and no collective action.
The world of tomorrow will be forged in the fiery crucible of the climate crisis and its myriad consequences on humankind. Unless we reach a shared understanding of each other and of the challenges facing us, we cannot hope to survive the Anthropocene, let alone to advance as a global civilization.
As part of my work on revenue strategy for Wikimedia, I imagined three scenarios about the world in 2031 and the organization’s place in it. I used these stories to spark discussions and shift conversations from day-to-day concerns and busywork to longer-term strategic thinking.
It is the year 2031, and Wikipedia is celebrating its 30th birthday. In a world of unrest and division, Wikipedia seems strangely united. Environmental disasters due to global warming, compounded by socioeconomic crises and identity politics, have birthed a world where distrust and fear of the other are the new normal. Bad actors have never been more active online, whether they are state-funded or attempting to destabilize nations. The violence in the streets is fueled by institutional censorship, organized disinformation, and trolling campaigns that make the online atmosphere even more polluted and toxic than the actual atmosphere.
Wikipedia has fared relatively well and looks, from afar, like a surprisingly quiet haven, whose content is stable and safe from harm. In trolls, censors, and purveyors of lies, Wikipedians have found a common enemy to unite them; in tech giants, they have found unexpected allies. Big Tech companies have invested heavily in technologies to combat bad actors: they have developed tools to circumvent censorship, to make sure that they still have access to their markets. They have devised ways to identify and derank information that is not from established reputable sources, to protect the content on which their business model relies from being poisoned. They have created shared reputation scores for internet users based on all the data they collect (which are now being tested by insurance companies as well), to determine who is trustworthy online.
Faced with a deluge of disinformation and editors acting in bad faith, most Wikipedia communities have erected social and technical dams. Entire countries are blocked from editing due to sustained cyberattacks. Administrators have access to checkuser information on all accounts except each other’s. Pages on all Wikipedias are now Trust-Protected: only Trusted editors can directly edit pages and approve edits from Untrusted users. Untrusted edits are held in a review queue for seven days before being automatically discarded, which happens to 92% of them; the review backlog had been growing exponentially before the automated flush was implemented. All the product improvements developed in the past twenty years to make it easier for newcomers to contribute have been counter-balanced by more stringent policies and heavy moderation tools developed in the last ten.
This War On Lies has not been without casualties. The knowledge and communities that had been systematically left out are excluded more than ever. Historical structures of power and privilege have been reinforced by algorithms and defensiveness. More people care about guarding the temple of knowledge than about asking whose knowledge it is. The discussion on expanding the definition of reliable sources was originally intended to find ways to bring more content to Wikipedia on topics not traditionally referenced in Western academic publications. The debate ended before it even started: in a world of fake newspapers and fabricated audiobooks, oral citations are a non-starter.
The reputation system built by tech companies suffers from systemic bias, notably because it was developed quickly based on the data available to them at the time. A recent effort to measure and address the reputation gap for Internet users from Africa unexpectedly resulted in an increase of the reputation scores of most of Europe’s population, which had apparently been consistently lower than those of North American citizens. Executives have promised to take another look at the reputation scores for African users in the future.
Wikipedia’s financial sustainability isn’t a huge concern at the moment. Although readership has declined dramatically, and content is now accessed more atomically through a multitude of unbranded interfaces, tech giants have stepped in to partly make up for the decrease in donations from readers. They can’t win this fight without Wikipedia’s armies of humans, who have proved to be critical in the arms race between bad actors and tech corporations. Most affiliates have disappeared, some due to lack of funding, and most due to changes in local legal landscapes that made any relation to Wikipedia dangerous for the individuals involved.
It is unclear how, when, or if the fight will end, but it has taken an undeniable toll on the health of communities: while they were originally energized by the righteousness of their mission to defend Wikipedia against the hordes, more and more of them are retiring from the wikis due to burnout, doxxing, or simply lack of enjoyment in contributing any more.
2031: Success into oblivion
More money than we had hoped, and the cost of success.
It is the year 2031, and Wikipedia is celebrating its 30th birthday. Hundreds of parties are happening around the world and on all continents. The Wikipedia Consortium can be proud of its achievements. We did it; we achieved the ambitious goals dreamed in the 2030 strategic direction. Looking back, our success can be attributed to a series of good decisions and external events that played in our favor, for better or for worse.
A series of earthquakes, tsunamis, and violent storms in Asia, combined with civil unrest due to economic downturn, created an extended shortage of computer chips, and a prolonged increase in the price of all technological hardware that weakened tech giants worldwide. Regulators seized this opportunity to strengthen antitrust laws and break down most of the largest tech corporations, in an effort to reassert state control and power that had been eroded in the previous two decades.
The weakening of the tech giants appeared as a blessing for the civil sector, and in particular the Wikimedia movement. Public distrust of large profit-driven corporations strengthened charities and other institutional actors that were appealing to civic-minded populations. Fundraising from small-dollar donors soared and unlocked major infrastructural investments to make Wikimedia content more accessible and embeddable into all the major devices and experiences that have emerged in the past ten years. As knowledge became more structured, bite-sized, and media-driven, the concept of the encyclopedia quickly disappeared. All Wikimedia projects were folded into the Wikipedia brand in 2024, and only the grumpiest old-timers insist on still calling it Wikimedia.
This opulence also empowered Wikimedia organizations to dramatically expand globally and set up a local presence in every region, except for Asia. The movement diversified into an array of foundations, chapters, for-profit subsidiaries, affiliates, and partners, all forming the Consortium. The fundraising manna and strategic alignment happened to combine with a societal desire for social justice and equity, fueled by the rising social, political, and economic power of Millennials and Gen-Zers. This convergence started a Golden Age of Equitable Collaboration, and a multitude of successful programs to include knowledge and communities that had been historically left out by structures of power and privilege.
Yet, some members of the Consortium are raising concerns about the future. Wikipedia has become the essential infrastructure of the ecosystem of free knowledge, and anyone who shares our vision would be able to join us—if only they knew that we exist.
As the margins of big tech corporations waned, so did their scruples and seemingly benevolent intentions. Their smaller size made them both more desperate and less subject to scrutiny: when faced with a choice between not being evil and not being at all, survival comes first. Content from Wikipedia is regularly remixed and presented through better experiences than what Wikipedia can offer, provided by companies free of ideological constraints of universality and privacy. Tech corporations are aggressively exploiting the digital commons without any desire to invest in its sustainability, in hopes of regaining ground in their quest for control and profit.
When we transformed into a platform that serves open knowledge to the world across interfaces and communities, we paved the way for our own disappearing act. Knowledge has been commodified and disintermediation is now total: hardly anyone visits Wikipedia sites directly any more. 94% of fact pulls are from automated programs. (Fact pulls replaced page views as the primary access metric in 2025.) With so few humans on the sites, and no way to contribute content from third parties, content growth has fallen to pre-2003 levels, which has seemingly solved most issues of community health. The glacial pace of contribution is only sustained by expensive outreach and contribution programs; incidentally, contributions from Latin America and Africa have surpassed those from Northern America and Europe, where no such programs were initially deemed necessary.
The global expansion of the Consortium has been costly and has committed most resources to illiquid assets. For-profit ventures, initially intended to serve as a mission-aligned way to generate revenue, are barely turning any profit: there is always someone else to make the same business model more profitable. Maintaining the human and technical infrastructure of the Consortium is putting a serious toll on the Money Bin accumulated through previous fundraising, and the financial reserves are running low. As the money hose dries up, long-standing squabbles of internal governance resurface, made worse by the Consortium’s sluggish bureaucracy.
As the celebrations wind down, optimism is widespread but the future is uncertain. The Consortium was a success for a while, but is it still?
2031: Human obsolescence
The robot revolution will not be advertised.
It is the year 2031, and Wikipedia is celebrating its 30th birthday. Banners and celebratory logos have been chosen through community contests, but they saw little participation. No one is really in the mood for celebrating: last month, Wikipedia was acquired by a large media group. And even though the new owners have promised editorial independence, the few remaining editors expect the giant to kill off the site in the next few years. How did we not see this coming?
The opening of the Northern Sea Route and Northwest passage in the 2020s, following the melting of the ice caps due to global warming, caused tensions between Arctic powers. With defense spending eating more and more of national budgets, governments have increasingly relied on large corporations to take on social services and infrastructure projects. Facing pressure from their constituents for more efficiency, regulators caved to the Big Tech lobby: artificial intelligence, connected devices, and smart everything appeared as modern solutions to do more with less government money and bureaucracy. The fact that the same companies were also some of the largest defense contractors, providing digital warfare and intelligence services, was not a coincidence.
Free of regulatory shackles and fueled by generous defense contracts, Big Tech made giant leaps in machine learning, instant translation, natural language processing, and general sensemaking engines. Similarly to technologies developed during the Space Race, these digital advances made their way into many everyday commercial products and further profited tech corporations.
All the while, the Wikimedia movement slowly made progress on its 2030 strategic direction, not realizing it had already slid into irrelevance: in a bloodless and silent coup, the machines had not only risen; they had already won.
While humans were slowly sifting through books to reference facts, machines were reading and making sense of millions of pages and integrating that knowledge into their databases. While humans were struggling to keep up with current events and news, machines were combing through millions of social media posts, data from devices and wearables, and assembling information that was more relevant, more local, and more timely. While humans were writing encyclopedia articles on the same topics in dozens of languages, machines were combining all of them into a structured, language-agnostic corpus that was then served to customers in their preferred tongue, through their interface of the moment, at the level of detail they needed. Any advances made by humans were quickly integrated into digital brains.
The machines and their powerful, wealthy human masters only needed to collaborate with humans until they had learned enough from them. We thought the threat was disintermediation: tech corporations appropriating knowledge from Wikimedia websites and serving it directly to their customers, cutting Wikimedia as the intermediary. Instead, the threat was that of human obsolescence: there is no need to cut the intermediary if you can assemble the knowledge yourself in the first place.
The jury is still out on systemic bias. The reliance on technology has in a way served as a Great Equalizer: knowledge is available to all, regardless of culture, region, or language. And ever since general sensemaking engines started being able to understand and organize local social data, knowledge and news from historically disenfranchised populations have entered the global knowledge corpus. However, long-standing structures of power and privilege can still be discerned by whoever cares enough to look: the machines and algorithms are still Children of Profit, and their creators have little incentive to make them auditable and accountable.
There might have been a future for Wikimedia if the movement had figured out its unique advantage over the machines and adapted in time, but by the time we realized what was happening, it was too late. Deprived of readers, and therefore of donors and contributors, the options for survival were few. Swallowing our pride, we were the ones who went to the media giant asking for help; they agreed to host us out of pity more than interest. The new owner isn’t even planning to serve ads on Wikipedia: the low number of readers (and therefore the meager revenue from ads) isn’t worth the trouble.
Beyond the scenarios
If all you’ve ever known is white swans, you think black ones can’t exist.
The point of this exercise was not to choose a scenario over another: we can’t choose what the future will look like, just like we can’t change the past. Our temporal agency is limited to the decisions we make in the present, based on our understanding of the past and the future. The goal was to provoke thinking, devise strategies, and guide decisions that would help us adapt to the variety of possible futures.
The scenarios all contained both favorable and unfavorable story elements, to ensure that people engaging with them wouldn’t be tempted to pick one as the future they favored. The actual future that would come to pass was likely to be a combination of elements from all these stories. These stories were the basis of the revenue strategy I devised in 2019.
During a department retreat, I organized a workshop with Advancement staff, using full-page cards representing story elements of the scenarios, to encourage long-term thinking while tapping into the participants’ own expertise and imagination. The cards provided the framework for the discussion, but let the participants weave them together in new ways.
I also introduced “black swan” cards halfway through the activity, picked at random among a few options. The goal was to prompt the participants to contend with unpredictable, wild card events and consider how their draft strategies would fare in those new circumstances.
The workshop was a high point of the retreat, and I’ve held similar workshops for Advancement and Wikimedia staff over the years. Future-oriented thinking helps build resilience by shifting the perspective of the organization’s leaders to the long view, and leading them to imagine the future consequences of current events and choices they make today.
Two years ago, I discovered that I was on the autism spectrum. As I learned more about myself and the way my brain worked, I started to look at past experiences through the lens of this newly-found aspect. In this essay, I share some of what I’ve learned along the way about my successes, my failures, and many things that confused me in the past, notably in my experiences in the Wikimedia movement.
This is a picture of me taken when I was 4, in nursery school, the French equivalent of Kindergarten.
I don’t have many memories about that time, but my parents remember that, while I wasn’t usually enthused about going to school during the week, I would often ask to go on Saturdays, because most of the other kids weren’t there.
It wasn’t that I didn’t like them; it was because the school was much quieter than during weekdays, and I had all the toys to myself. I didn’t have to interact with other children, or share the pencils, or the room. I could do whatever I wanted without worrying about the other kids.
I didn’t know it at the time, but it would take me nearly 30 years to look back at this story and understand how it made complete sense.
I’m now 32 years old, and a lot has changed. Two years ago, after some difficulties at work, my partner decided to share his suspicions that I might be on the autism spectrum. I knew little about it at the time, but it was a hypothesis that seemed to explain a lot, and seemed worth exploring.
Sure, the subject had come up before a few times, but it was always as a joke, an exaggeration of my behavior. I never thought that label applied to me. One problem is that autism is usually represented in a very uniform manner in popular culture. Movies like Rain Man feature autistic savants who, although they have extraordinary abilities, live in a completely different world, and sometimes aren’t verbal. The autism spectrum is much more diverse than those stereotypical examples.
After I started researching the topic, and reading books on autism or autobiographies by autistic people, I realized how much of it applied to me.
It took a bit longer (and a few tests) to get a confirmation from experts, and when it came, many people still had doubts. The question that came up the most often was “But how was this never detected before?” Autism is generally noticed at a much younger age, and it seemed that for most of my life, I had managed to disguise myself as “neurotypical,” meaning someone whose brain works similarly to most people.
The current prevailing hypothesis to explain this, based on an IQ test taken as part of the evaluation process, is that I am privileged to have higher-than-average intellectual capacities, which have allowed me to partly compensate for the different wiring of my brain. One way to illustrate this is to use a computer analogy: in a way, my CPU runs at a higher frequency, which has allowed me to emulate with software the hardware that I’m missing. What this also means is that it can be exhausting to run this software all the time, so sometimes I need to be by myself.
As you can imagine, realizing at 31 that you are on the autism spectrum changes your perception dramatically; everything suddenly starts to make sense. I’ve learned a lot over the past two years, and this increased metacognition has allowed me to look at past events through a new lens.
In this essay, I want to share with you some of what I’ve learned, and share my current understanding of how my brain works, notably through my experience as a Wikimedian.
One caveat I want to start with is that autism is a spectrum. There’s a popular saying among online autistic communities that says: “You’ve met an autistic, you’ve met one autistic.” Just keep this in mind: What I’m presenting here is based on my personal experience, and isn’t going to apply equally to all autistic people.
The picture above was taken during Wikimania 2007 in Taipei. I was exploring the city with Cary Bass (User:Bastique) and a few other people. Looking back at this picture now, there are a few things I notice today:
I’m wearing simple clothes, because I have absolutely no sense of fashion, and those are “safe” colors.
I’m carrying two bags (a backpack and a photo bag), because I always want to be prepared for almost anything, so I carry a lot of stuff around.
I’m sitting down to change a lens on my camera, because it’s a more stable position to avoid dropping and breaking expensive gear. I’ve learned that this habit of using very stable positions is actually a mitigating strategy that I developed over the years without realizing it, to compensate for problems with balance and motor coordination.
A good analogy to help understand what it’s like to be autistic in a neurotypical society is to look at Mr. Spock, in the Star Trek Original Series. The son of a Vulcan father and a human mother, Spock is technically half-human, but it is his Vulcan side that shows the most in its interactions with the crew of the Enterprise.
Some of the funniest moments of the show are his arguments with the irascible Dr. McCoy, who calls him an “unfeeling automaton” and “the most cold-blooded man [he’s] ever known.” To which Spock responds: “Why, thank you, Doctor.” 
As a Vulcan, Spock’s life is ruled by logic. Although he does feel emotions, they are deeply repressed. His speech pattern is very detached, almost clinical. Because of his logical and utilitarian perspective, Spock often appears dismissive, cold-hearted, or just plain rude to his fellow shipmates.
In many ways, Spock’s traits are similar to autism, and many autistic people identify with him. For example, in her book Thinking in Pictures, Temple Grandin, a renowned autistic scientist and author, recounts how she related to Spock from a young age:
Many people with autism are fans of the television show Star Trek. […] I strongly identified with the logical Mr. Spock, since I completely related to his way of thinking.
I vividly remember one old episode because it portrayed a conflict between logic and emotion in a manner I could understand. A monster was attempting to smash the shuttle craft with rocks. A crew member had been killed. Logical Mr. Spock wanted to take off and escape before the monster wrecked the craft. The other crew members refused to leave until they had retrieved the body of the dead crew member. […]
I agreed with Spock, but I learned that emotions will often overpower logical thinking, even if these decisions prove hazardous.
In this example, and in many others, Spock’s perception filter prevents him from understanding human decisions mainly driven by emotion. Those actions appear foolish or nonsensical, because Spock interprets them through his own lens of logic. He lacks the cultural background, social norms and unspoken assumptions unconsciously shared by humans.
The reverse is also true: Whenever humans are puzzled or annoyed by Spock, it is because they expect him to behave like a human; they are often confronted with a harsher truth than they would like. Humans interpret Spock’s behavior through their own emotional perception filter. They often misunderstand his motives, assume malice and superimpose intents that change the meaning of his original words and actions.
You’re probably familiar with the conceptual models of communication. In many of those models, communication is represented as the transmission of a message between a sender and a receiver.
If you apply this model to an oral conversation, you quickly see all the opportunities for miscommunication: From what the sender means, to what they actually say, to what the receiver hears, to what they understand, information can change radically, especially when you consider nonverbal communication. It’s like a 2-person variation of the telephone game. In the words of psychologist Tony Attwood:
Every day people make intuitive guesses regarding what someone may be thinking or feeling. Most of the time we are right but the system is not faultless. We are not perfect mind readers. Social interactions would be so much easier if typical people said exactly what they mean with no assumptions or ambiguity.
If this is the case for neurotypical people, meaning people with a “typical” brain, imagine how challenging it can be for autistics like me. A great analogy is given in the movie The Imitation Game, inspired by the life of Alan Turing, who is portrayed in the film as being on the autism spectrum.
Historical accuracy aside, one of my favorite moments in the movie is when a young Alan is talking to his friend Christopher about coded messages. Christopher explains cryptography as “messages that anyone can see, but no one knows what they mean, unless you have the key.”
A very puzzled Alan replies:
How is that different from talking? […] When people talk to each other, they never say what they mean, they say something else. And you’re expected to just know what they mean. Only I never do.
Autistic people are characterized by many different traits, but one of the most prevalent is social blindness: We have trouble reading the emotions of others. We lack the “Theory of mind” used by neurotypical people to attribute mental states (like beliefs and intents) to others. We often take things literally because we’re missing the subtext: it’s difficult for us to read between the lines.
Liane Holliday Willey, an autistic author and speaker, once summarized it this way:
You wouldn’t need a Theory of Mind if everyone spoke their mind.
Many languages have a common phrase to ask someone how they’re doing, whether it’s the French Comment ça va ?, the English How are you? or the German Wie geht’s?
When I first moved to the US, every time someone asked me “How are you?,” I would pause to consider the question. Now, I’ve learned that it’s a greeting, not an actual question, and I’ve mostly automated the response to the expected “Great, how are you?.” It only takes a few milliseconds to switch to that path and short-circuit the question-answering process. But if people deviate from that usual greeting, then that mental shortcut doesn’t work any more.
A few weeks ago, someone in the Wikimedia Foundation office asked me “How is your world?,” and I froze for a few seconds. In order to answer that question, my brain was reviewing everything that was happening in “my world” (and “my world” is big!), before I realized that I just needed to say “Great! Thanks!.”
Privilege and pointed ears
This is only one of the challenges faced by autistic people, and I would now like to talk about neurotypical privilege. I’m a cis white male, and I was raised in a loving middle-class family in an industrialized country. By many standards, I’m very privileged. But, despite my superpowers, being autistic in a predominantly neurotypical society does bring its lot of challenges.
The most common consequence I’ve noticed in my experience, and in accounts from other autistic people, is a feeling of profound isolation. The lack of Theory of mind and the constant risk of miscommunication make it difficult to build relationships. It’s not anyone’s fault in particular; it’s due to a general lack of awareness.
Imagine that you’re talking to me face to face. You don’t really know me, but I seem nice so you start making small talk. I’m not saying much, and you need to carry the discussion over those awkward silences. When I do speak, it’s in a very monotone manner, like I don’t really care. You try harder, and ask me questions, but I hesitate, I struggle to maintain eye contact, and I keep looking away, as if I’m making stuff up as I go.
Now this is what’s happening from my perspective: I’m talking to someone I don’t really know well, but you seem nice. I don’t know what to talk about, so I keep quiet at first. Silences aren’t a problem: I’m just happy to be in your company. I don’t have very strong feelings about what we’re talking about, so I’m speaking very calmly. You’re asking me questions, and of course it takes a while to think about the correct answer. All this “eye contact” thing that I learned in school is taking a lot of mental resources that would be better used to compute the answer to your question, so I sometimes need to look away to better focus.
This illustrates one of many situations in which each person’s perception filter caused a complete disconnect between how the situation was perceived on each side.
There are also many professional hurdles associated with being on the autism spectrum, and autistics are more affected by unemployment than neurotypicals . I’m privileged in that I’ve been able to find an environment in which I’m able to work, but many autistics aren’t so lucky. It’s been well documented that people in higher-up positions aren’t necessarily the best performers, but often people with the best social skills.
With that in mind, imagine what the career opportunities (or lack thereof) can be for someone who is a terrible liar, who has a lot of interest in doing great work, but less interest in taking credit for it, who doesn’t understand office politics, who not only makes social missteps and angers their colleagues, but doesn’t even know about it, someone who’s unable to make small talk around the office. Imagine that person, and what kind of a career they can have even if they’re very good at their job.
Casual relationships with colleagues and acquaintances are usually superficial; the stakes of the water cooler discussions are low, so people are more inclined to forgive missteps. However, friendship is another matter, and for most of my life, I have hardly had any friends, unless you use Facebook’s definition of the term. Awkwardness is generally tolerated, but rarely sought after. It’s not “cool.”
Most of those issues arise because you don’t have a way of knowing that the person in front of you is different. At least Spock had his pointed ears to signal that he wasn’t human. His acceptance by the crew of the Enterprise was in large part due to the relationships he was able to develop with his shipmates. Those relationships would arguably not have been possible if they had not known how he was different.
Let me go back to that conceptual model of face-to-face communication. Now imagine how this model changes if you’re communicating online, by email, on wiki, or on IRC. All those communication channels, that Wikimedians are all too familiar with, are based on text, and most of them are asynchronous. For many neurotypicals, these are frustrating modes of communication, because they’re losing most of their usual nonverbal signals like tone, facial expressions, and body language.
However, this model of computer-mediated communication is much closer to the communication model of autistics like me. There is no nonverbal communication to decrypt; less interaction and social anxiety; and usually, no unfamiliar environment either. There are much fewer signals, and those that remain are just words; their meaning still varies, but it’s much more codified and reliable than nonverbal signals.
What there is online, instead, is plenty of time, time that we can use to collect our thoughts and formulate a carefully crafted answer. Whereas voice is synchronous and mostly irreversible, text can be edited, crafted, deleted, reworded, or rewritten until it’s exactly what we want it to be; then we can send it. This is true of asynchronous channels like email and wikis, but it also extends to semi-synchronous tools like instant messaging or IRC.
It’s not all rainbows and unicorns, though. For example, autistics like me are still very much clueless about politics and reading between the lines. We tend to be radically honest, which doesn’t fly very well, whether online or offline. autistics are also more susceptible to trolling, and may not always realize that the way people act online isn’t the same as the way they act in the physical world. The Internet medium tends to desensitize people, and autistics might emulate behavior that isn’t actually acceptable, regardless of the venue.
Autism in the Wikimedia community
Of course, one major example of wide-scale online communication is the Wikimedia movement. And at first glance, Wikimedia sites, and Wikipedia in particular, offer a platform where one can meticulously compile facts about their favorite obsession, or methodically fix the same grammatical error over and over, all of that with limited human interaction; if this sounds like a great place for autistics (and a perfect honey trap) well, it is to some extent.
For example, my first edit ten years ago was to fix a spelling error. My second edit was to fix a conjugation error. My third edit was to fix both a spelling and a conjugation error. That’s how my journey as a Wikipedian started ten years ago.
Wikipedians are obsessed with citations, references, and verifiability; fact is king, and interpretation is taboo. As long as you stay in the main namespace, that is. As soon as you step out of article pages and venture into talk pages and community spaces like the “Village Pump,” those high standards don’t apply any more. There are plenty of unsourced, exaggerated and biased statements in Wikipedia discussions.
That’s in addition to the problems I mentioned earlier. As an autistic, it can be hard to let go of arguments about things or people you care about. It’s often said that autistic people lack empathy, which basically makes us look like cold-hearted robots. However, there is a distinction between being able to read the feelings of other people, and feeling compassion for other people.
Neurotypical people have mirror neurons that make you feel what the person in front of you is feeling; autistic people have a lot fewer of those, which means they need to scrutinize your signals and try to understand what you’re feeling. But they’re still people with feelings.
If you’re interested in learning more about autism in the Wikimedia community, there’s a great essay on the English Wikipedia, which I highly recommend. One thing it does really well is avoiding the pathologization of autism, and instead insisting on neurodiversity, meaning autism as a difference, not a disease.
Steve Silberman, who wrote a book on the history of autism, presented it this way:
One way to understand neurodiversity is to think in terms of human operating systems: Just because a PC is not running Windows doesn’t mean that it’s broken.
By autistic standards, the normal human brain is easily distractible, obsessively social, and suffers from a deficit of attention to detail.
But still, neurodiversity has a cost. Sometimes, you’ll be offended; sometimes, you’ll be frustrated; and sometimes, you’ll think “Wow, I would never have thought of that in a million years.”
As I mentioned earlier, I believe Spock was only able to build those relationships over time because people were aware of his difference, and learned to understand and embrace it. Spock also learned a lot from humans along the way.
My goals here were to raise awareness of this difference that exists in our community, to encourage us to discuss our differences more openly, and to improve our understanding of each other.
There is a lot I didn’t get into in this essay, and I might expand on specific points later. In the meantime, I’m available if you’re interested in continuing this discussion, and you should feel free to reach out to me, whether in person or online.
In 2014, I posted a few photos, I continued to work on technical communications at Wikimedia before a role change, I learned more about myself, I moved to California, and I hiked a lot.
2014 in failures
Let’s begin with what didn’t work and get it out of the way. In January 2014, I started posting some of my photos on this site. I have accumulated tens of thousands of photos over the past eight years, but published only a small fraction of them. By starting to publish a selection of them here, my goal was to create a momentum that would encourage me to process my backlog and publish my collections here and on Wikimedia Commons.
The momentum didn’t really last, though, and I ended up stopping after posting only seven photo articles. In retrospect, I think the issue wasn’t really the photos themselves, but rather the accompanying texts. I’ve acknowledged this failure, and recently decided to retire the “Photo” section of this website. The photos are still online, but I’ve removed the navigation shortcut to that section.
I may resume posting photos in the future, although it’s not a priority at the moment. If I do, I might change the format of the posts and only feature the photos with a very short text, if any.
2014 in work
During most of 2014, I continued to work as Technical Communication Manager at the Wikimedia Foundation, the nonprofit that operates Wikipedia.
Part of this work involved reviewing technical posts for the Wikimedia blog; I notably edited and published a series of candid essays written by students who participated in the Google Code-in program. In their “discovery reports”, they outlined their first steps as members of the Wikimedia technical community, and provided a newcomer’s perspective on tools and processes regularly used by experienced contributors.
I attended the Zürich hackathon, as well as Wikimania, the annual Wikimedia conference, whose 2014 edition was in London. At Wikimania, I presented on Tech News and put together a poster so that attendees could learn about it even if they couldn’t attend the presentation.
In September, my role at the Wikimedia Foundation changed, and I started working on other projects, most notably the File metadata cleanup drive. The drive is an initiative to decrease the number of files (on Wikimedia sites) whose information can’t be read by programs.
2014 in self-discovery
2013 had been a turning point for me, in that I had discovered that I was likely on the autistic spectrum. In 2014, a few experts officially confirmed that hypothesis. When asked why this had not been detected earlier in my life, the prevailing hypothesis was that I had unknowingly compensated this social blindness by a higher potential, as suggested by tests performed in 2013. I like to think of it as having my my own emulated emotion chip.
Throughout 2014, I continued to research and read on this topic. Doing so, I’ve continued to better understand my blind spots, and explored what I now refer to as my “super-powers”, a fancy way of characterizing the unique way in which my brain works.
Notably, I started reading on a variety of specialized topics I was not familiar with but intrigued me. Doing so, I discovered that I was very fast at picking up and understand new concepts and disciplines. I had had a feeling that that was the case for a long time, but experimenting with this skill was particularly fun and rewarding (I’ve recently been reading about Civil engineering and Human spaceflight).
2014 in transatlantic move
The biggest change in 2014 was our emigration from France to the US. As part of my role change at the Wikimedia Foundation, I relocated to the San Francisco Bay Area (again). The relocation process was easier this second time around, in part because my partner was able to relocate with me this time, and also because we decided to get organized.
Transitioning from a completely-remote environment to a tech open-space has required some adjustments, but overall we’re very happy to have relocated.
2014 in physical activity
I do go outside sometimes, and as someone intrigued by the concept of Quantified Self, I try to keep metrics about my life whenever possible. Physical activity is one of the easiest things to track thanks to dedicated mobile apps.
I love to hike and I occasionally run. In 2014, I knew we were going to relocate to sunny California, so I decided to take advantage of the snowy Alps while we were still in France.
It had been years since I had skied downhill, but after a couple of days it all came back and I enjoyed it a lot. I also started snowshoeing, which was a really nice complementary activity. Where downhill skiing involves sprints and adrenalin, snowshoeing involves endurance and beautiful lesser-used forest trails.
Hiking (inc. snowshoeing)
The year ahead
2015 is already well underway, but it’s not too late to mention what I’m planning to do this year.
Regarding my work at the Wikimedia Foundation, I’m continuing to lead the File metadata cleanup drive, and I’m hoping to continue to drive down the number of files missing machine-readable metadata. I also have a few smaller projects in the pipeline, notably the Template taxonomy.
Regarding personal work and recreation, I’ve started to learn Spanish again. My goal is to be able to handle basic communication by Summer, when I may visit Mexico City. Hopefully, by then, I’ll be able to say more than “¡Hola!”, “Soy una tortuga” and “El elefante come la manzana”.
I’ve also decided to learn to play the piano; we’ll see how far I can go in one year. Considering that I’m a total beginner, I can only make progress!
Last, I intend to continue to populate this site with historical and new content. My current priority at the moment is finishing to write about past projects before embarking on new ones, but I do think there will be room to post new content before next year’s “year in review” post.
Where our heroes embark on their second move a quarter of a world away, but not before planning it thoroughly.
In previous episodes
I lived in San Francisco for a year in 2009–2010, when I first started working for the Wikimedia Foundation on the Multimedia Usability Project. Unfortunately, I had to move back to France because my partner couldn’t get a visa at the time.
When I first came to the US, I didn’t have a bank account, a social security number, or a credit history. My knowledge and understanding of American culture was limited to what could be gleaned from movies and TV series.
In 2009, we spent the first few nights after we arrived in a hotel, and our reservation ended before we could find a place. We managed to find temporary accommodation for two more weeks, which gave us enough time to find the apartment where I lived for a year.
I remember this period being a very stressful time because of all the uncertainty. Last year, I was offered the opportunity to transition to a new position at the Wikimedia Foundation, and as a consequence to relocate (back) to San Francisco. When we made the decision to come live in the Bay Area again, we also decided to do things differently this time around.
A staged process
Any move requires planning. Moving to a new country 9,400 km away (5,800 miles) requires a lot of planning.
A critical issue when moving is usually that, during the same time period, you need to leave your place, and find a new one, and do all that while packing your belongings.
Instead, we decided to decouple the “leaving Toulouse” part from the “arriving in San Francisco” part. Our visas wouldn’t be ready until September, but we decided to leave Toulouse in July. The plan was to stay at my father’s house in Normandy during the transition period.
Having this buffer period turned out to be a great decision. It allowed us to focus on leaving our place in Toulouse without having to worry about finding a place just yet, and it gave us a lot of flexibility with regard to shipping our belongings and flying to San Francisco.
My father’s house in Normandy was going to be mostly unused during that period, and living in Normandy for a few months would also be an opportunity to catch up with the rest of the family.
Leaving our old apartment in Toulouse was the easy part. We gave notice to our landlord and scheduled our milestones based on when we’d be leaving. Because we didn’t have to worry about finding a new place just yet, or choosing what to take with us to the US, it made things a lot simpler.
There were few parking spaces in the street of our apartment building, so we needed to park the moving van directly on the street. We contacted the city services in advance and they allowed us to temporarily block traffic in the street while we loaded everything.
One thing we didn’t expect, though, was that “having permission to park on the street” didn’t actually mean “being able to park there”. It turned out that work on the utility lines was happening in our street at the same time, and on moving day the whole street was filled with trucks, vans and other heavy equipment.
In the end, we managed to squeeze in our van during the workers’ lunch break. We loaded it in a record one hour, thanks to half a dozen friends of friends who came to give us a hand at the last minute.
A few months in the Normandy countryside
We arrived in Normandy the next day and proceeded to set up our living quarters at my father’s. It took a little skill to essentially merge two homes into one, so some of the boxes lasted a bit longer than expected, but we managed to set up our own space without disrupting the house’s equilibrium too much.
As we settled in, we also made a few improvements, notably to organize the house a bit more.
We had never stayed in this house more than a few days at a time, mostly for the holidays. This time, we were able to take advantage of the beautiful Summer weather to explore the area on the week-ends.
I also went through some of my old stuff to clear out boxes, notes from college, and generally put my affairs in order before leaving, since I knew we wouldn’t be able to come back very often (or very long).
As October approached, we started focusing on preparing the second leg of our move, and finding a place in the San Francisco bay area. We quickly realized that the pace at which Craigslist ads were being posted and taken down meant that we’d have to be on site to do any kind of proper house-hunting. The good news was that we could leave Normandy at any time, since we didn’t have to give notice.
Arriving and settling in in the Bay Area
Knowing from experience that we’d need a few weeks to find a home, we looked for temporary accommodation on Airbnb from France, and stayed in Berkeley when we arrived.
This time around, we didn’t have to worry about setting up a bank account and getting a social security number, so that made things a bit easier. We still didn’t have a credit history, though, so many Craigslist postings were out of our reach.
We eventually found a great place in the North Bay that was both affordable and in a great setting, and we’ve been living there since.
Cultural acclimation has been smoother this time, partly due to having lived here before. The excellent “Life in the USA” site has been of great help as well. Touted as “the complete web guide to American life for immigrants and Americans”, it has provided us with incredible insight into the American culture, and I recommend it to anyone who’s immigrating to the US. Also, this time my partner was able to get a visa (thank you, United States v. Windsor) so this has obviously made the transition much less stressful.
Living in the North Bay involves a longer commute than when I was living downtown, but this hasn’t been a deal-breaker so far. I would obviously like to be able to live closer to work, but I’m currently willing to have a long commute if that means living in a quiet area and in a more affordable home. (The rent of the one-bedroom I used to rent in San Francisco has doubled since 2010.)
It’s now been four months since we moved, and we’re mostly settled. We’ve had to adapt our routines to a new set of constraints, but we’re glad we moved. We hope to explore the area a bit more as Spring and Summer approach, and roam the beautiful parks and trails of northern California.
42,812. That’s the number of files currently residing in my “photos” folder. They span seven years of photography, three continents, and an evolving mix of taste, experience and equipment. This mosaic marks the inauguration of the gallery section of this site, where I’ll be sharing the pictures I like the most.
To be fair, many of the photos sitting in my hard drive are similar to each other. I often take series of nearly-identical pictures to increase the likelihood of getting at least one good shot out of the lot. This can be, for example, when taking photos in low light without stabilization, or when photographing a moving subject like a flying plane, a running squirrel or a babbling politician. There’s also, in the lot, quite a bit of actual duplicates that exist in different formats.
Nonetheless, that’s a fair amount of photos, and I’m slowly sorting, rating, tagging, describing, geolocating and uploading them all (mostly to Wikimedia Commons). One thing I’ve noticed that helps me process my photos is to have a routine, like dedicating a few hours every week to that activity. It can be a pretty intense and exhausting task, though, and I’m probably more likely to stick to it if I do it for shorter periods of time but more regularly.
Therefore, I’ve opened a dedicated gallery section on this site, where I’ll be posting some of my photos a few times a week (ideally, once a day, but I’ll start with a less ambitious goal).
To inaugurate this gallery, it seemed fitting to start with a representative sample of my body of work so far. I’ve therefore created a photographic mosaic, i.e. a photograph made of thousands of smaller photographs, picked for their color and composition, and assembled to reconstruct the pattern and color of a larger picture.
The mosaic above shows the “Painted Ladies“: famous Victorian houses near Alamo Square, in San Francisco. It’s composed of 22,059 of my other pictures, automatically picked by a program from the pool of 42,812. I used the excellent (and open-source) Metapixel tool to prepare the images and assemble the mosaic. Below is the original photo I took in June 2010.
The original photo is quite ordinary, and yet I really like the mosaic that was generated from it. The mosaic almost transforms the picture into a pointillism painting, which makes it much more interesting. The mosaic’s colors appear washed out compared to some of the saturated colors of the original, but it actually contributes to the painting appearance.
It’s my first time making a photo mosaic, so I’ve experimented a bit with the settings but didn’t dive into them too much. For example, the small pictures composing the mosaic are all squares, regardless of their original aspect ratio (usually 3:2 or 2:3, or 4:3 for my older photos), which means that nearly all of them are squeezed. It’s not too much of a problem in this case, but I’ll want to retry assembling mosaics while conserving the images’ ratio. There’s a minimal distance of 50 between identical images, but several items of a series may be closer. I’ve also slightly favored chrominance over luminance in the color matching algorithm.
I’ve experimented with different pattern images, i.e. the source image whose pattern is reconstructed from the smaller ones. I like some of the other resulting mosaics, so I’ve included them below. I have a few others, but today I’ll stick to the San Francisco theme.
Below is a mosaic showing the famous Golden Gate Bridge, seen from San Francisco’s Presidio. It’s composed of 11,094 pictures. The original photo actually made it to Wikimedia Commons a mere five weeks after it was taken.
This mosaic is a bit more vibrant than the one of the Painted Ladies, because the original image is more saturated. I like the original because it has strong red-green-blue components, but the strong blue mostly disappears in the mosaic. The original also contains more color gradients, which don’t look so nice in the mosaic; the whole sky is pretty noisy, and the artistic vignetting is exacerbated, particularly in the lower right corner.
Part of the sky’s noise is due to the minimal distance of 50 images between two identical ones: this causes groups of images to be repeated in waves that become noticeable from afar. It’s possible to increase the minimal distance, however that drastically increases the processing time needed to create the mosaic.
The third and last mosaic (below) shows the same issues of gradients and repeating waves in the sky and sea; you can compare with the original. However, it highlights something that isn’t obvious in the previous mosaic, and that’s the impressive quality of Metapixel’s matching algorithm, which makes it possible to make out the bridge’s suspension system, and even individual cables. I’m also quite fond of the grain added by the mosaic to the rusty chain and pillars in the foreground.
To wrap up: I like the additional potential of creativity provided by mosaics as a medium, and I’ll probably play with them again in the future. But for now, after this introduction, I’ll start posting individual photos, many of which have been hinted at in the mosaics. I’ve quite enjoyed rediscovering forgotten pictures as I was exploring the super-high resolution versions of the mosaics, and I hope you’ll enjoy them as well, as they start popping up in this gallery.
If you’ve ever wanted to be kept informed of technical changes likely to impact your Wikimedia experience, you’ll want to subscribe to Tech News, a weekly newsletter than can be delivered directly to your talk page.
The amount of technical activity happening across the Wikimedia movement as well as the number of different discussion venues make it increasingly more difficult and time–consuming to monitor changes relevant to one’s involvement in Wikimedia projects. Understanding technical issues and discussions is especially hard since they contain a lot of jargon terms and are mostly conducted only in English.
Tech News is intended to make it easier to keep track of such noteworthy changes and understand them better. By using jargon–free language, we aim to reach regular Wikimedia contributors who are most likely to be affected by upcoming software and configuration changes.
The newsletter is assembled by Tech ambassadors, a group of technically-minded volunteers who help other Wikimedians with technical issues, and act as bridges between developers and local wikis. They’re the ones who monitor technical changes across numerous (and scattered) channels and put together the high-level, plain English summary.
Volunteer translators are the other unsung heroes of Tech News. They’ve been doing an amazing job, which we are very thankful for: not only have they translated every issue so far into around 10 languages on Meta-Wiki (making the newsletter available for users speaking languages other than English), but their responsiveness has even allowed us to distribute translated versions of the newsletter to subscribers on their wikis.
Four issues of the newsletter have been published so far, and the response has been overwhelmingly positive. Heartwarming comments have for instance described the newsletter as “clear, concise and useful info all in one.” Readers have generally welcomed the initiative, and have provided feedback that helped us further improve the format of the newsletter.
The Wikipedia Signpost has already started making use of Tech News, and we’re hoping that, along with their counterparts in other languages, the Signpost writers will join forces with us to monitor technical changes.
There are a few ways in which you can contribute to Tech News: by translating the latest issue into your language, adding relevant information or links to the next issue, or just by sharing the news with your community.
The second volume of the Architecture of Open-Source Applications book, which includes a chapter on MediaWiki, is now available online and on lulu.com.
The Architecture of Open-Source Applications is a collection of technical essays detailing the architecture of twenty-four major open-source applications. This is the second volume of a series that aims to help developers understand how great and large programs are constructed, and the decisions (or accidents) that led to the way they now work. The series draws inspiration from books used by architects that feature case studies of the great buildings of history.
This volume contains a chapter detailing the inner workings of MediaWiki, the wiki software that powers all Wikimedia sites, including Wikipedia. The writing of the chapter was coordinated by myself and Sumana Harihareswara. While I put together the majority of the content, it wouldn’t have been possible without the initial knowledge-sharing effort made by many Wikimedia engineers and volunteer MediaWiki developers, who also reviewed and improved the several revisions that the text underwent.
Greg Wilson and Amy Brown, the book’s editors, contacted the Wikimedia Foundation in August 2011 to offer to feature MediaWiki in the second volume. We chose a very collaborative approach to writing the chapter to ensure that the content was accurate and thorough, and also to split the workload among subject matter experts.
This is the second book published this year that contains a chapter written by Wikimedia staff, after the publication of Open Advice, a collection of essays, stories and lessons learned by members of the Free Software community.
I hope the chapter on MediaWiki, and also the rest of the book, will prove useful and interesting to the Wikimedia community and other developers. If you enjoyed it, learned from it, or would like to see more publications of this type, let us know!
About 50 authors from many different projects of the free software community were brought together by Lydia Pintscher, the book’s editor, who started the project in early 2011.
A year and 380 pages later, the book is now available, and tries to provide an answer to the question: What’s the key thing you would have liked to know when you started contributing?
Authors answer that question for many topics, ranging from “Writing patches” to “Documentation for Novices,” to business models, conferences, translation, design, and more.
I contributed “Learn from your users,” a chapter on user experience and usability testing. You’ll also recognize other names from the Wikimedia community, like Evan Prodromou, Markus Krötzsch and Felipe Ortega. You can learn more about the book and the authors on the book’s website.