Katherine Louise Bouman (; born 1989) is an American engineer and computer scientist working in the field of computational imaging. She led the development of an algorithm for imaging black holes, known as Continuous High-resolution Image Reconstruction using Patch priors (CHIRP), and was a member of the Event Horizon Telescope team that captured the first image of a black hole. The California Institute of Technology, which hired Bouman as an assistant professor in June 2019, awarded her a named professorship in 2020. In 2021, asteroid 291387 Katiebouman was named after her. In 2024, she became an associate professor. == Early life and education == Bouman grew up in West Lafayette, Indiana. Her father, Charles Bouman, is a professor of electrical and computer engineering and biomedical engineering at Purdue University. As a high school student, Bouman conducted imaging research at Purdue University. She graduated from West Lafayette Junior-Senior High School in 2007. Bouman studied electrical engineering at the University of Michigan and graduated summa cum laude in 2011. She earned her master's degree in 2013 and obtained a doctoral degree in electrical engineering and computer science in 2017 from the Massachusetts Institute of Technology (MIT). At MIT, she was a member of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). This group also worked closely with MIT's Haystack Observatory and with the Event Horizon Telescope. She was supported by a National Science Foundation Graduate Fellowship. Her master's thesis, Estimating Material Properties of Fabric through the Observation of Motion, was awarded the Ernst Guillemin Award for best Master's Thesis in electrical engineering. Her Ph.D. dissertation, Extreme imaging via physical model inversion: seeing around corners and imaging black holes, was supervised by William T. Freeman. Prior to receiving her doctoral degree, Bouman delivered a TEDx talk, How to Take a Picture of a Black Hole, which explained algorithms that could be used to capture the first image of a black hole. == Research and career == After earning her doctorate, Bouman joined Harvard University as a postdoctoral fellow on the Event Horizon Telescope Imaging team. Bouman joined Event Horizon Telescope project in 2013. She led the development of an algorithm for imaging black holes, known as Continuous High-resolution Image Reconstruction using Patch priors (CHIRP). CHIRP inspired image validation procedures used in acquiring the first image of a black hole in April 2019, and Bouman played a significant role in the project by verifying images, selecting parameters for filtering images taken by the Event Horizon Telescope, and participating in the development of a robust imaging framework that compared the results of different image reconstruction techniques. Her group is analyzing the Event Horizon Telescope's images to learn more about general relativity in a strong gravitational field. Bouman received significant media attention after a photo, showing her reaction to the detection of the black hole shadow in the EHT images, went viral. Some people in the media and on the Internet misleadingly implied that Bouman was a "lone genius" behind the image. However, Bouman herself repeatedly noted that the result came from the work of a large collaboration, showing the importance of teamwork in science. Bouman also became the target of online harassment, to the extent that her colleague Andrew Chael made a statement on Twitter criticizing "awful and sexist attacks on my colleague and friend", including attempts to undermine her contributions by crediting him solely with work accomplished by the team. Bouman joined the California Institute of Technology (Caltech) as an assistant professor in June 2019, where she works on new systems for computational imaging using computer vision and machine learning. In 2024, she was promoted to associate professor of computing and mathematical sciences, electrical engineering and astronomy as well as a Rosenberg Scholar. Bouman received a named professorship at Caltech in 2020. In 2021, Bouman was awarded the Royal Photographic Society Progress Medal and Honorary Fellowship. == Recognition == She was recognized as one of the BBC's 100 women of 2019. In 2024, Bouman was awarded a Sloan Research Fellowship.
Motor theory of speech perception
The motor theory of speech perception is the hypothesis that people perceive spoken words by identifying the vocal tract gestures with which they are pronounced rather than by identifying the sound patterns that speech generates. It originally claimed that speech perception is done through a specialized module that is innate and human-specific. Though the idea of a module has been qualified in more recent versions of the theory, the idea remains that the role of the speech motor system is not only to produce speech articulations but also to detect them. The hypothesis has gained more interest outside the field of speech perception than inside. This has increased particularly since the discovery of mirror neurons that link the production and perception of motor movements, including those made by the vocal tract. The theory was initially proposed in the Haskins Laboratories in the 1950s by Alvin Liberman and Franklin S. Cooper, and developed further by Donald Shankweiler, Michael Studdert-Kennedy, Ignatius Mattingly, Carol Fowler and Douglas Whalen. == Origins and development == The hypothesis has its origins in research using pattern playback to create reading machines for the blind that would substitute sounds for orthographic letters. This led to a close examination of how spoken sounds correspond to the acoustic spectrogram of them as a sequence of auditory sounds. This found that successive consonants and vowels overlap in time with one another (a phenomenon known as coarticulation). This suggested that speech is not heard like an acoustic "alphabet" or "cipher," but as a "code" of overlapping speech gestures. === Associationist approach === Initially, the theory was associationist: infants mimic the speech they hear and that this leads to behavioristic associations between articulation and its sensory consequences. Later, this overt mimicry would be short-circuited and become speech perception. This aspect of the theory was dropped, however, with the discovery that prelinguistic infants could already detect most of the phonetic contrasts used to separate different speech sounds. === Cognitivist approach === The behavioristic approach was replaced by a cognitivist one in which there was a speech module. The module detected speech in terms of hidden distal objects rather than at the proximal or immediate level of their input. The evidence for this was the research finding that speech processing was special such as duplex perception. === Changing distal objects === Initially, speech perception was assumed to link to speech objects that were both the invariant movements of speech articulators the invariant motor commands sent to muscles to move the vocal tract articulators This was later revised to include the phonetic gestures rather than motor commands, and then the gestures intended by the speaker at a prevocal, linguistic level, rather than actual movements. === Modern revision === The "speech is special" claim has been dropped, as it was found that speech perception could occur for nonspeech sounds (for example, slamming doors for duplex perception). === Mirror neurons === The discovery of mirror neurons has led to renewed interest in the motor theory of speech perception, and the theory still has its advocates, although there are also critics. == Support == === Nonauditory gesture information === If speech is identified in terms of how it is physically made, then nonauditory information should be incorporated into speech percepts even if it is still subjectively heard as "sounds". This is, in fact, the case. The McGurk effect shows that seeing the production of a spoken syllable that differs from an auditory cue synchronized with it affects the perception of the auditory one. In other words, if someone hears "ba" but sees a video of someone pronouncing "ga", what they hear is different—some people believe they hear "da". People find it easier to hear speech in noise if they can see the speaker. People can hear syllables better when their production can be felt haptically. === Categorical perception === Using a speech synthesizer, speech sounds can be varied in place of articulation along a continuum from /bɑ/ to /dɑ/ to /ɡɑ/, or in voice onset time on a continuum from /dɑ/ to /tɑ/ (for example). When listeners are asked to discriminate between two different sounds, they perceive sounds as belonging to discrete categories, even though the sounds vary continuously. In other words, 10 sounds (with the sound on one extreme being /dɑ/ and the sound on the other extreme being /tɑ/, and the ones in the middle varying on a scale) may all be acoustically different from one another, but the listener will hear all of them as either /dɑ/ or /tɑ/. Likewise, the English consonant /d/ may vary in its acoustic details across different phonetic contexts (the /d/ in /du/ does not technically sound the same as the one in /di/, for example), but all /d/'s as perceived by a listener fall within one category (voiced alveolar plosive) and that is because "linguistic representations are abstract, canonical, phonetic segments or the gestures that underlie these segments." This suggests that humans identify speech using categorical perception, and thus that a specialized module, such as that proposed by the motor theory of speech perception, may be on the right track. === Speech imitation === If people can hear the gestures in speech, then the imitation of speech should be very fast, as in when words are repeated that are heard in headphones as in speech shadowing. People can repeat heard syllables more quickly than they would be able to produce them normally. === Speech production === Hearing speech activates vocal tract muscles, and the motor cortex and premotor cortex. The integration of auditory and visual input in speech perception also involves such areas. Disrupting the premotor cortex disrupts the perception of speech units such as plosives. The activation of the motor areas occurs in terms of the phonemic features which link with the vocal track articulators that create speech gestures. The perception of a speech sound is aided by pre-emptively stimulating the motor representation of the articulators responsible for its pronunciation . Auditory and motor cortical coupling is restricted to a specific range of neuronal firing frequency. === Perception-action meshing === Evidence exists that perception and production are generally coupled in the motor system. This is supported by the existence of mirror neurons that are activated both by seeing (or hearing) an action and when that action is carried out. Another source of evidence is that for common coding theory between the representations used for perception and action. == Criticisms == The motor theory of speech perception is not widely held in the field of speech perception, though it is more popular in other fields, such as theoretical linguistics. As three of its advocates have noted, "it has few proponents within the field of speech perception, and many authors cite it primarily to offer critical commentary".p. 361 Several critiques of it exist. === Multiple sources === Speech perception is affected by nonproduction sources of information, such as context. Individual words are hard to understand in isolation but easy when heard in sentence context. It therefore seems that speech perception uses multiple sources that are integrated together in an optimal way. === Production === The motor theory of speech perception would predict that speech motor abilities in infants predict their speech perception abilities, but in actuality it is the other way around. It would also predict that defects in speech production would impair speech perception, but they do not. However, this only affects the first and already superseded behaviorist version of the theory, where infants were supposed to learn all production-perception patterns by imitation early in childhood. This is no longer the mainstream view of motor-speech theorists. === Speech module === Several sources of evidence for a specialized speech module have failed to be supported. Duplex perception can be observed with door slams. The McGurk effect can also be achieved with nonlinguistic stimuli, such as showing someone a video of a basketball bouncing but playing the sound of a ping-pong ball bouncing. As for categorical perception, listeners can be sensitive to acoustic differences within single phonetic categories. As a result, this part of the theory has been dropped by some researchers. === Sublexical tasks === The evidence provided for the motor theory of speech perception is limited to tasks such as syllable discrimination that use speech units not full spoken words or spoken sentences. As a result, "speech perception is sometimes interpreted as referring to the perception of speech at the sublexical level. However, the ultimate goal of these studies is presumably to understand the neural processes supporting the ability to process spee
Opposition to AI data centers
Since 2024, dozens of local community-led protest campaigns have emerged in opposition to AI data centers. == Motivations == Organized opposition to AI data centers has been driven by concerns about energy use, energy costs, noise pollution, air pollution, and water waste. Opposition sentiment is widespread with a Gallup poll conducted in March 2026 showing that 70% of respondents oppose the construction of new AI data centers in their neighborhood. == Impact == In 2025, local opposition to AI data centers led to the delay or cancellation of projects totalling US$156 billion. == Specific protests and outcomes in the United States == According to Data Center Watch, there are has been a wave of dozens of protests against AI data centers since 2022. Below is a non-exhaustive list of some notable examples. === Goodyear and Buckeye, Arizona: Tract AI Data Center Proposal === In Goodyear and Buckeye, Arizona, a $14 billion project by developer Tract was withdrawn after local authorities blocked necessary rezoning in response to pressure from resident organizers. Opponest stiff resistance due to concerns over building heights, noise pollution, and the potential strain on local utilities. However, the company announced a revised project near the Buckeye airport in August 2024, with the backing of local officials and the mayor. === Peculiar, Missouri: Diode Ventures Harper Road Technology Park Proposal === In Peculiar, Missouri, residents from the group "Peaceful Peculiar" organized to stop a data center proposal from Diode Ventures called Harper Road Technology Park. Citing concerns around noise and light pollution, health, environmental impacts, jobs, property values, and energy use, organizers attended local planning and zoning meetings in large numbers and lobbied councilors to reject the proposal. Ultimately, the city council unanimously rejected the proposal in September 2024. === Chesterton, Indiana: Provident Realty Advisors Proposal === In Chesterton, Indiana, the Texas-based company Provident Reality Advisors applied for a $1.3 billion construction of a data center complex on the Brassie Golf Club property. Provident Realty Advisors wanted to purchase the 200 acres owned by PPM Chesterton LLC in 2024 order to build a data center complex, with eight buildings and an end user of a hyperscaler. The Town Council of Chesterton released a statement saying that they would never support this project, at least not at the scale and location it was planned for. They cited fears of added noise for locals, electrical or water management concerns, the intrusiveness of a data center built next to houses, and more. Provident released a statement shortly after rescinding their plan, because it was clear than the town of Chesterton would not support them. === Cascade Locks, Oregon: Roundhouse Digital Infrastructure Proposal === Startup data center developer Roundhouse Digital Infrastructure had planned to build out a 10-megawatt data center using a vacant industrial building and nearby 10-acre site in the Port of Cascade Locks, Oregon. After significant organized community opposition, the project was abandoned. === Forth Worth, Texas: WUSF 5 Rock Creek East Proposal === In September 2024, the City Council of Fort Worth, Texas approved a zoning change that would allow construction of a data center. In responses, neighbors mounted opposition citing concerns about traffic, light pollution, energy consumption, water use, and noise issues if the data center were to be built. In response to extensive public comments opposing a tax break for the data center, a city councilor withdrew his motion to approve the tax break. As of April, 2026, the future of the project is still uncertain. === Santa Clara, California: GI Partners Proposal === GI partners sought to build a new AI data center in Santa Clara, California, which is already home to many data centers, by acquiring a conditional permit use that would have allowed the developer to knock down a property and replace it with a data center. To obtain this permit they were required to go before members of the Planning Commission. Ultimately, the project was delayed with the Planning Commission requiring GI partners to do more public outreach. === Virginia === ==== Richmond: DC Blox Proposal ==== After residents organized to lobby the municipal government to block the proposal to avoid noise pollution and higher energy use, commissioners denied the company's permit. ==== Catlett Station: Headwaters Site Proposal ==== In Catlett, Virginia, developer Headwaters proposed construction of a data center complex just north of the town in 2020. In response, a residents' organization called "Protect Catlett" was formed to oppose the project. Arguments against the data center involved its impacts on water and power availability, its noise as a residential disturbance, and its destruction of historic and community heritage buildings. Arguments in favor cited job creation and $20 million in local tax revenue if the project were to go through. Protect Catlett utilized town halls and public comments to mobilize opposition to the project. They also dedicated time to educating other residents about the project's negative impacts and canvassing door-to-door in order to garner even more opposition to the project. Ultimately, after fervent opposition from most town residents, the project was canceled by the town and the developer. ==== Culpeper County: Culpeper Acquisitions Proposal ==== Culpeper Acquisitions, LLC, proposed a massive $12 billion data center project in Culpeper County, Virginia, designed to feature 4.6 million square feet of space across nine multi-story buildings. Coalition to Save Culpeper (C2SC) is an activist organization formed to resist the development of the project. C2SC has been active on many fronts including, messaging on social media, reaching out to local officials, and organizing meetings to bring community members with aligned interests together. Ultimately, the project was delayed due to unanimous denial by the Culpeper County Planning Commission on June 12, 2024, which was driven by intense opposition from C2SC. C2SC was successful in their mission largely because they were able to get so many people from the community behind it, and put enough pressure on local officials to take action. ==== Midlothian: Province Group Proposal ==== In late October 2025, the Powhatan County Board of Supervisors in Virginia voted unanimously to approve the $3 billion data center, despite the county's Planning Commission having unanimously recommended denial several days earlier. The reasoning behind their support for the center is that it will generate substantial tax revenue, reducing the county's reliance on residential property taxes. This appeal of lowering residential property taxes is the major selling point for the center's development. The developer, California-based Province Group, incentivized the Board by being agreeable to its conditions for building the center. The center is still on track for development, but faces local resistance, though little information is available on specific groups opposing it. ==== Warrenton: Amazon Proposal ==== Citizens for Farquier County (CFFC) advocates to "preserve the natural, historic and agricultural resources" of their county. Historically, this has meant opposing the building of a dam or lights in front of fast food stores. This group has recently mobilized in opposition of a plan to build data centers for Amazon. They first filed a suit to stop the construction in 2023 and it has been in litigation ever since. The case hinges on opposition to a 2021 zoning amendment which allowed data centers to be built in town. CFFC's lawyer, Dale Mullen, argues that this amendment violates state law, which requires such amendments to state their "public purpose". They argue that the permit for the Amazon data center was "void from the beginning". The CFFC also organized to vote out town council members who approved the first data center and were up for reelection, replacing them with candidates who opposed the data center. In May 2025, after attending town council meetings to speak out against the data center, the planning commission voted 4–1 to remove the zoning amendment allowing data center construction in town, citing public opposition. Currently, CFFC is advocating along with Piedmont Environmental Group, for phasing out data center tax breaks at the state level. ==== France: Marseille opposition ==== In France, local opposition materialised in response to proposed data centre developments, especially in and around the city of Marseille. Opposition came from activists, such as "Clouds Were Under Our Feet" group, residents ,and local politicians. Issues raised related to energy use, environmental impact, and limited local benefits (such as the creation of a few jobs only). == Legislation in the United States == Legal limits and moratoriums on the construction of new d
Abu Dhabi Autonomous Racing League
The Abu Dhabi Autonomous Racing League (A2RL) is an autonomous racing league based in Abu Dhabi and organized by ASPIRE, part of the UAE government's Advanced Technology Research Council. It has three distinct categories: the "car race", the drone race, and the buggy race. The first car race was held on 27 April 2024 at the Yas Marina Circuit, marking the first major autonomous formula race outside the US since the now-folded Roborace championship. The first drone race was held on 11 and 12 April 2025. == Formats == A2RL has three distinct formats, the formula racing format (dubbed the Car Race), the quadcopter drone racing format (dubbed the Drone Race), and the off-road dune buggy racing format (dubbed the Buggy Race). === Car Race === A2RL's main event, the car race is a standard formula racing format with self-driving formula cars. The cars are made by Dallara and are modified versions of Super Formula cars with Yokohama tires. These cars had the CPUs of their AIs mounted where the driver's seat is on a non-modified chassis, as well as hydraulic actuators for AI control of the vehicle, multiple sensor systems including LIDAR and GPS, and a large LED indicator showing the status of the AI. The first car race was held on 27 April 2024. This race was marked by the cars' subpar performance: Out of four cars that qualified, only two finished the race - the other two did not. The next race was held on 15 November 2025, with 11 teams. ==== Technical specifications ==== The full list of technical specifications are as follows: Chassis: Dallara EAV24 (modified Dallara SF23) Forward suspension: Pushrod type, torsion bar spring, adjustable dampers, third element Rear suspension: Pushrod type, torsion bar, coil springs, adjustable dampers, third element Tires: Yokohama Advan Drive-by-wire system: Provided by Meccanica 42, the DBW system consists of steering and brake actuators, with a central ECU that coordinates the driving actions and reacts to any critical situation in real-time. Brakes: Brembo calipers, Brembo carbon discs, electro-hydraulically activated Engine: 4 Piston Racing K20C1 (based on Honda 2.0l; turbocharged 4-cylinder engine) Gearbox: 3MO 6-speed gearbox Sensor suite: 7x Sony IMX728 cameras, 4x ZF ProWave radar units, 3x Seyond Falcon Kinetic lidar units Main computer: Neousys RGS-8805GC ==== Races held ==== === Drone Race === Created in partnership with the Drone Champions' League, the drone race is the quadcopter drone racing aerial format of the A2RL. The first race was held on 11/12 April 2025 at the ADNEC Marina Hall. 10 teams are scheduled to take part. === Buggy Race === The buggy race will be the off-road format of the A2RL using self-driving dune buggies. No date or number of teams has been announced for the first race. === Other events === A2RL is known to host AI vs AI and Human vs AI events, in Abu Dhabi and abroad. One such event took place at the Suzuka Circuit in Japan. The Human vs AI race was precluded due to AI car "Yalla" crashing into the wall during the formation lap. == Team lists ==
Lymphater's Formula
"Lymphater's Formula" (Polish: "Formula Lymphatera") is a 1961 science fiction short story by Polish writer Stanisław Lem. It is a story of a "mad scientist", mathematician Ammon Lymphater, who invents an artificial intelligence, and then he realizes that it is capable of rendering the humankind obsolete. It was first published in the 1961 collection Księga robotów (Book of Robots) with the pre-annotation "from the memoirs of Ijon Tichy". The story was never republished with this pre-annotation, and nothing in the novel gives any indication at Ijon Tichy. Piotr Krywak tried to figure out possible explanations for this, apart from a typographical error. == Plot == Ammon Lymphater became interested in the emerging science of cybernetics and information theory, and started studying the works of an animal brain, the ant's brain in particular. He took note that the inherited knowledge is an evolutionary advantage somehow not exploited in full by the evolution. Eventually he came to a conclusion that only by pure biological restrictions that adaptive abilities of insects were stopped in their tracks by the evolution. He went on further wondering whether the ants have an ability to apriori knowledge, i.e., knowledge neither inherited nor learned. He decided to consult a famous myrmecologist, who told him about a rare ant species Acanthis Rubra Willinsoniana with an exceptionally high adaptability. Eventually Lymphater devised and constructed "It" capable of instant precognition of everything within "Its" rapidly expanding range of perception. From "It" Lymphater learns that the humanity is not the "crown of evolution", but rather evolution's tool to create "It", because the evolution could not create "It" directly (confirming Lymphater's reasoning about ants). Realizing that the Superentity "It" renders the human civilization redundant and obsolete, Lymphater destroys "It". "It" already knew Lymphater's intentions, but was not worried, knowing that sooner or later someone else will create "It" again and again. "It" was only the first variant of Lymphater's formula and the second variant is possible. Lyphater wonders whether the second one would be capable to create the third stage of the evolution which would amount to an artificial God. == Publication history == It was translated in Russian (as "Формула Лимфатера") in 1963, in Hungarian (as "Lymphater utolsó képlete") in 1966, and in Bulgarian (as "Формулата на Лимфатер" by Георги Димитров Георгиев) in 1969. In 1973 an audiobook was released in German (as "Die lymphatersche Formel"), narrated by Martin Held. It was also republished (and translated) in some other collections of Lem's short stories.
Virtual Woman
Virtual Woman is a software program that has elements of a chatbot, virtual reality, artificial intelligence, a video game, and a virtual human. It claims to be the oldest form of virtual life in existence, as it has been distributed since the late 1980s. Recent releases of the program can update their intelligence by connecting online and downloading newer personalities and histories. == Program play == When Virtual Woman starts, the user is presented with a list of options and then may choose their Virtual Woman's ethnic type, personality, location, clothing, etc. or load a pre-built Virtual Woman from a Digital DNA file. Once the options are determined, the user is presented with a 3-D animated Virtual Woman of their selection and then can engage them in conversation, progressing in a manner similar to that of its predecessor, ELIZA and its successors, the chatbots. In most versions of Virtual Woman, this is done through the keyboard, but some versions also support voice input. == In popular culture == Software sales and usage statistics from private companies are difficult to verify. WinSite, an independent Internet shareware distribution site that does publish public download counts, has for some time now listed some version of Virtual Woman in their top three shareware downloads of all time with well over seven hundred thousand downloads. == Compadre == The group of beta testers and advisers for Virtual Woman are referred to as Compadre and have their own beta testing site and forum. == Criticisms == As Virtual Woman has developed the ability to conduct longer and more realistic interactions, particularly in recent beta releases, criticism has arisen that this may lead some users to social isolation, or to use the program as a substitute for real human interaction. However, these are criticisms that have been leveled at all video games and at the use of the Internet itself. == Release history == Versions of Virtual Woman with rough release dates and PC platforms for which they were designed: Virtual Woman (????) (DOS) Virtual Woman for Windows (1991) (Windows 3.0) Virtual Woman 95 (1995) (Windows 3X, Windows 95) Virtual Woman 98 (1998) (Windows 3X, Windows 95) Virtual Woman 2000 (2000) (Windows 95+) Virtual Woman Millennium (Windows 95, XP) Virtual Woman Net ( Windows XP/Vista specific)
Akoma Ntoso
Akoma Ntoso (Architecture for Knowledge-Oriented Management of African Normative Texts using Open Standards and Ontologies, AKN) is an international technical standard for representing legal documents (executive, legislative, and judiciary) in a structured manner using a domain specific, legal XML vocabulary. The term akoma ntoso means "linked hearts" in the Akan language of West Africa. Akoma Ntoso is a legal document standard designed to serve as a basis for modern machine-readable and fully digital legislative and judicial processes. This is achieved by providing a coherent syntax and well-defined semantics to represent legal documents in a digital format. It is designed to be suitable as a common exchange format in all parliamentary, legal and judicial systems around the world. Taking advantage of the shared heritage present in all legal systems, Akoma Ntoso has been developed to have ample flexibility to respond to all the differences in texts, languages, and legal practices. Aiming to expand on certain common practices, the standard therefore has a broad scope. It includes a common extensible model for data (the document content) and metadata (such as bibliographic information and annotations). Specifically, as a common legal document standard for the interchange of legal documents it is designed to be highly flexible in its support of documents and functionalities, maintaining a large set of both structural and semantic building blocks (over 500 entities in version 3.0) for representing this wide variety of document types of virtually all legal traditions. It is extensible in order to allow for modifications to address the individual criteria of organizations or unique aspects of various legal practices and languages without sacrificing interoperability with other systems. Akoma Ntoso is as such part of a wider approach to developing open, non-proprietary technical standards for structuring legal documents and information under the name of Legal XML, which also includes formats and standards for, e.g., eContracts, eNotarization, electronic court filings, the technical representation of legal norms and rules (LegalRuleML) or technical standards for the interfaces of, e.g., litigant portal exchange platforms. Akoma Ntoso allows machine-driven processes to operate on the syntactic and semantic components of digital parliamentary, judicial and legislative documents, thus facilitating the development of high-quality information resources. It can substantially enhance the performance, accountability, quality and openness of parliamentary and legislative operations based on best practices and guidance through machine-assisted drafting and machine-assisted (legal) analysis. Embedded in the environment of the semantic web, it forms the basis for a heterogenous yet interoperable ecosystem, with which these tools can operate and communicate, as well as for future applications and use cases based on digital law or rule representation. == Definition == The Akoma Ntoso standard defines a set of machine readable electronic representations in XML format of the building blocks of parliamentary, legislative and judiciary documents. As official self-description, the standard (...) defines a set of simple, technology-neutral electronic representations of parliamentary, legislative and judiciary documents for e-services in a worldwide context and provides an enabling framework for the effective exchange of "machine readable" parliamentary, legislative and judiciary documents such as legislation, debate record, minutes, judgements, etc. Providing access to primary legal materials, parliamentary works and judiciaries documents is not just a matter of giving physical or on-line access to them. "Open access" requires the information to be described and classified in a uniform and organized way so that content is structured into meaningful elements that can be read and understood by software applications, so that the content is made "machine readable" and more sophisticated applications than on-screen display are made possible. The standard is composed of: an XML vocabulary that defines the mapping between the structure of legal documents and their equivalent in XML; specifications of an XML schema that defines the structure of legal documents in XML. They provide rich possibilities of description for several types of parliamentary, legislative and judiciary document, such as bills, acts and parliamentary records, judgments, or gazettes; a recommended naming convention for providing unique identifiers to legal sources based on FRBR model; a MIME type definition. == History and adoption == Akoma Ntoso started as an UNDESA project in 2004 within the initiative "Strengthening Parliaments' Information Systems in Africa". Its core vocabulary was created mostly by Monica Palmirani and Fabio Vitali, two professors from the Centre for Research in the History, Philosophy, and Sociology of Law and in Computer Science and Law (CIRSFID) of the University of Bologna. A first legislative text editor supporting Akoma Ntoso was developed in 2007 on the base of OpenOffice. In 2010 European Parliament developed an open source web-based application called AT4AM based on Akoma Ntoso for facilitating the production and the management of legislative amendments. Thanks to this project, the application of Akoma Ntoso could be extended to new type of documents (e.g. legislative proposal, transcript) and to other scenarios (e.g., multilingual translation process). Akoma Ntoso also was explicitly designed to be compliant with CEN Metalex, one of the other popular legal standards, which is used in the legislation.gov.uk. In 2012, the Akoma Ntoso specifications became the main working base for the activities of the LegalDocML Technical Committee within the LegalXML member section of OASIS. The "United States Legislative Markup" (USLM) schema for the United States Code (the US codified laws), developed in 2013, and the LexML Brasil XML schema for Brazilian legislative and judiciary documents, developed before, in 2008, were both designed to be consistent with Akoma Ntoso. The United States Library of Congress created the Markup of US Legislation in Akoma Ntoso challenge in July 2013 to create representations of selected US bills using the most recent Akoma Ntoso standard within a couple months for a $5000 prize, and the Legislative XML Data Mapping challenge in September 2013 to produce a data map for US bill XML and UK bill XML to the most recent Akoma Ntoso schema within a couple months for a $10000 prize. The National Archives of UK converted all the legislation in AKN in 2014. The availability of bulk legislation "moved the UK's ranking from fourth to first, in the 2014 Global Open Data Index, for legislation". The Senate of Italian Republic provides, since July 2016, all the bills in Akoma Ntoso as bulk in open data repository. The German Federal Ministry of the Interior started the project Elektronische Gesetzgebung ("Electronic Legislation") in 2015/2016 and published Version 1.0 of the German application profile "LegalDocML.de" in March 2020. The projects aim is to digitalize the entire legislative lifecycle from drafting to publication. Germany decided to adopt a model-driven development approach to creating and providing a subschema-based application profile in order to ensure interoperability among organizationally independent actors, each with their respective IT landscapes and tools. In this initial version LegalDocML.de covers draft bills in the form of laws, regulations and general administrative directives. As part of an ongoing development process, the standard could incrementally be expanded in future stages to include all relevant document types of parliamentary, legislative and promulgation processes and tools. The High-Level Committee on Management (HLCM), part of the United Nations System Chief Executives Board for Coordination, set up a Working Group on Document Standards that approved in April 2017 to adopt Akoma Ntoso as standard for modeling its documentation. Akoma Ntoso in its version 1.0 is finally adopted as OASIS standard in the frame of LegalDocML in August 2018.