Data Thinking is a framework that integrates data science with the design process. It combines computational thinking, statistical thinking, and domain-specific knowledge to guide the development of data-driven solutions in product development. The framework is used to explore, design, develop, and validate solutions, with a focus on user experience and data analytics, including data collection and interpretation The framework aims to apply data literacy and inform decision-making through data-driven insights. == Major components == According to "Computational thinking in the era of data science": Data thinking involves understanding that solutions require both data-driven and domain-knowledge-driven rules. Data thinking evaluates whether data accurately represents real-life scenarios and improves data collection where necessary. The framework highlights the importance of preserving domain-specific meaning during data analysis. Data thinking incorporates statistical and logical analysis to identify patterns and irregularities. Data thinking involves testing solutions in real-life contexts and iteratively improving models based on new data. The process requires evaluating problems from multiple abstraction levels and understanding the potential for biases in generalizations. == Major phases == === Strategic context and risk analysis === Analyzing the broader digital strategy and assessing risks and opportunities is a common step before beginning a project. Techniques like coolhunting, trend analysis, and scenario planning can be used to assist with this. === Ideation and exploration === In this phase, focus areas are identified, and use cases are developed by integrating organizational goals, user needs, and data requirements. Design thinking methods, such as personas and customer journey mapping, are applied. === Prototyping === A proof of concept is created to test feasibility and refine solutions through iterative evaluation to optimize for effective performance. === Implementation and monitoring === Solutions are tested and monitored for performance and continual improvement. == Implementing Data Thinking == The following resources explain more about data thinking and its applications: "Data Thinking: Framework for data-based solutions" by StackFuel "What is Data Thinking? A modern approach to designing a data strategy" by Mantel Group "Data Science Thinking" by SpringerLink These sources provide detailed insights into the methodology, phases, and benefits of adopting Data Thinking in organizational processes.
Tradeshift
Tradeshift is a cloud based business network and platform for purchase-to-pay automation, supply chain payments, marketplaces, virtual cards and supply chain financing. Its 2018 round of funding, led by Goldman Sachs, raised US$250 million at a valuation of $1.1 billion, giving the company unicorn status. Tradeshift is headquartered in San Francisco, California and has offices in London, Copenhagen, Bucharest and Kuala Lumpur. Tradeshift has reprocessed over $1 trillion USD through transactions on its network. == History == Tradeshift was founded in 2010 by Christian Lanng, Mikkel Hippe Brun, and Gert Sylvest. Inspiration for Tradeshift came after they created the world's first large scale peer-to-peer infrastructure for an e-business called NemHandel. The founders also had leading roles (Governing board member, Technical Director) in the European Commission project PEPPOL inside the European Union. In 2010, the Tradeshift platform launched in May in Copenhagen. Tradeshift won the European Startup Awards in the category of "Best Business or Enterprise Startup." In 2011, Tradeshift made its app marketplace available. In 2012, Tradeshift moved their headquarters from Copenhagen to San Francisco. In 2013, Tradeshift opened an R&D center in Suzhou, China. Tradeshift opened an additional office in London. And LATAM e-invoicing capabilities were added through partnership with Invoiceware. In 2014, Tradeshift expanded with offices in Tokyo, Paris, and Munich. The EU Commission officially approved the Universal Business Language (UBL) data format – a format Tradeshift supports – as eligible for referencing in tenders from public administrations. In 2015, Tradeshift won the Circulars "Digital Disruptor" Award at the WEF conference in Davos, Switzerland. Tradeshift also acquired product information management company Merchantry, and launched e-procurement and supplier risk management solutions. In 2016, Tradeshift acquired Hyper Travel and secured a $75 million series-D round funding. In 2017, Tradeshift acquired IBX Business Network and launches Tradeshift Ada. In 2018, Tradeshift secured a $250 million series-E round funding. and launched Blockchain Payments, the latter as part of Tradeshift Pay. In December 2018 Tradeshift acquired Babelway, an online B2B integration platform. The acquisition added three new office locations to Tradeshift (Salt Lake City, Louvain-la-neuve, Belgium, Cairo Egypt). In Q3 2018, Tradeshift reported year-over-year revenue growth of 400%, new bookings growth of 284%, and gross merchandise volume (GMV) growth of 262%. New total contract value also grew by US$47 million. Additionally, it added 27 new customers including Hertz, Shiseido, ECU and multiple Fortune 500 companies. In July 2023, HSBC and Tradeshift announced an agreement to launch a new, jointly owned business focused on the development of embedded finance solutions and financial services apps. As part of the agreement, HSBC made a $35 million investment into Tradeshift and joined its board. The agreement was part of a funding round which is expected to raise a minimum of $70 million from HSBC and other investors. The new joint venture will allow HSBC and Tradeshift to deploy a range of digital solutions across Tradeshift and other platforms. This includes payment and fintech services embedded into trade, e-commerce and marketplace experiences. In September 2023, CEO Lanng was fired for "gross misconduct on multiple grounds," including "allegations of sexual assault and harassment." Tradeshift was alleged to have fired his accuser after she complained to the company's human resources department, its co-founders and members of its board of directors about his abuse. == Financials == The company's valuation as of May 2018 was $1.1 billion. Tradeshift is now considered a unicorn, and, according to Bloomberg, will not need any further funding. Jan 14, 2020, Tradeshift announced that they had raised $240 million in Series F finance. == Acquisitions == In 2015, Tradeshift acquired product information management company Merchantry. Merchantry is a retail product information management (PIM) software for multi-vendor ecommerce retailers. In 2016, Tradeshift acquired Hyper Travel. Hyper Travel is a travel management service that allows customers to access travel agents via its native messaging apps, SMS, and email. In 2017, Tradeshift acquired IBX Group. In 2018, Tradeshift acquired Babelway, an online B2B integration platform.
Digital zombie
A digital zombie is a person so engaged with digital technology or social media they are unable to separate themselves from a persistent online presence. Writing in 2017, University of Sydney researcher Andrew Campbell expressed concerns over whether or not the individual can truly live a full and healthy life while they are preoccupied with the digital world. Other individuals have also begun referencing certain types of behaviour with being a digital zombie. Stefanie Valentic, managing editor of EHS Today, refers to it as people hunting digital creatures through their smartphones in public spaces, always fixed on their phones. The University of Warwick has used the term to argue that further research needs to be done with people who exist in digital form after death to help people grieve their loss. == Modern applications == === Distracted walking === The term digital zombie can refer to a person performing distracted walking, which has been labelled dangerous by the American Academy of Orthopaedic Surgeons. They created the "Digital Deadwalkers" campaign after physicians became aware of the risks associated with walking across intersections and sidewalks while paying attention only to smartphones and not one's surroundings. Also stating that the name is derived from the fact that "they're oblivious to everyone else, so it's like they're dead-walking, sleepwalking." === Living through media === The Department of Sociology, University of Warwick has also identified the term, digital zombie, to refer to an individual who has died but is digitally resurrected, reanimated and socially active. These digital zombies do things in death they did not do when they were alive as they "live" again through a digital self on a digital medium. Dead celebrities sometimes become digital zombies when they are reanimated to appear in commercial advertisements (such as Audrey Hepburn and Bob Monkhouse). Other accidental digital zombies include Tupac Shakur and Michael Jackson who were both digitally resurrected and recreated to perform "live" on stage years after their death. Researchers at the University of Warwick have carried out research into the area of human-computer interaction. in an effort to understand the affect these digital zombies have on grief and bereavement. === Mobile gaming === Writer for EHS Today, Stefanie Valentic, has made observations with the mobile phone video game Pokémon Go, which offers players the experience to hunt and collect digital creatures called Pokémon through their smartphone in real world. Players can be observed simultaneously gazing at their phone while also obliviously walking around their environments looking for Pokémon. Stefanie references these individuals as "digital zombies" since they walk around with no cognition of their surroundings while engaged with their phone. == Health risks == === Heavy use of technology === Research by the University of Sydney has begun looking at how new technology such as digital media and smartphones impact our lives and questioning whether they can create new compulsions and obsessions. The research demonstrates that increased heavy technological use can have negative health consequences similar to drugs, smoking, and alcohol. Marcel O'Gorman, an associate professor of English at the University of Waterloo, has commented on the body of research examining how technology impacts cognition, stating currently that there is no empirical evidence to support any theories that suggest that technology can damage memory and attention span. === Heightened risk to children === Manfred Spitzer, a German psychiatrist, has raised concerns with providing digital devices to children. During the early childhood stage while their brains are rapidly growing, increased exposure to digital devices may deprive them of necessary development required to facilitate brain growth. These concerns are also shared by Korean doctors who believe giving digital devices, like smartphones to children, limits their cognitive development.
Variable-message sign
A variable- (also changeable-, electronic-, or dynamic-) message sign or message board, often abbreviated VMS, VMB, CMS, or DMS, and in the UK known as a matrix sign, is an electronic traffic sign often used on roadways to give travelers information about special events. Such signs warn of traffic congestion, accidents, incidents such as terrorist attacks, Amber/Silver/Blue Alerts, roadwork zones, or speed limits on a specific highway segment. In urban areas, VMS are used within parking guidance and information systems to guide drivers to available car parking spaces. They may also ask vehicles to take alternative routes, limit travel speed, warn of duration and location of the incidents, inform of the traffic conditions, or display general public safety messages. == History == VMS systems were deployed at least as early as the 1950s on the New Jersey Turnpike. The road's signs of that period, and up to around 2012, were capable of displaying a few messages in neon, all oriented around warning drivers to slow down: "REDUCE SPEED", followed by a warning of either construction, accident, congestion, ice, snow, or fog at a certain distance ahead. The New Jersey Turnpike Authority replaced those signs (along with 1990s-vintage dot-matrix VMS systems along the Garden State Parkway) with more flexible electronic signs between 2010 and 2016. The current VMS systems are largely deployed on freeways, trunk highways, or in work zones. On the interchange of I-5 and SR 120 in San Joaquin County, California, an automated visibility and speed warning system was installed in 1996 to warn traffic of reduced visibility due to fog (where tule fog is a common problem in the winter), and of slow or stopped traffic. Message Signs were deployed in Ontario during the 1990s and are now being upgraded on 400-series highways as well as two pilot secondary highways in northeastern Ontario. == Technologies and types == Early variable message signs included static signs with words that would illuminate (often using neon tubing) indicating the type of incident that occurred, or signs that used rotating prisms (trilons) to change the message being displayed. These were later replaced by dot matrix displays typically using eggcrate, fiber optic, or flip-disc technology, which were capable of displaying a much wider range of messages than earlier static variable message signs. Since the late 1990s, the most common technology used in new installations for variable message signs are LED displays. In recent years, some newer LED variable message signs have the ability to display colored text and graphics. Dot-matrix variable message signs are divided into three subgroups: character matrix, row matrix, and full matrix. In a character matrix VMS, each character is given its own matrix with equal horizontal spacing between them, typically with two or three rows of characters. In a full matrix VMS, the entire sign is a single large dot matrix display, allowing the display of different fonts and graphics. A row matrix VMS is a hybrid of the two types, divided into two or three rows like a character matrix display, except each row is a single long dot matrix display instead of being split per character horizontally. Overhead variable message signs are today available in three form factors: front access, rear access, and walk-in. In a front access variable message sign, maintenance is performed by lifting the sign open from the front. Most smaller VMS are of the front access form factor, and are typically installed today on major arterials. The rear access form factor is similar to the front access form factor, except that maintenance is performed from the rear of the sign, and are commonly used for medium-sized dynamic message signs installed along the roadside of freeways (instead of overhead). The walk-in form factor is a more recent introduction, where maintenance on the sign is performed from the inside of the sign. A key advantage of the walk-in form factor is that lane closures are generally not required to perform maintenance on the sign. Most of the largest VMS units installed today are walk-in units, and are typically installed overhead on freeways. The NJ Turnpike Authority counts five unique types of variable message signs under its jurisdiction, at least one of which has been replaced by newer signs. They are: "REDUCE SPEED" neon signs (1950s-2010, obsolete, have now been replaced). "Changeable message signs" (trilon/ rotating-drum signs that can be used for closing roads or moving traffic to other roadways). Electronic VMS: signs with remotely controlled messages displayed on them; the messages are sent from the State Traffic Management Center, updating the signs automatically. Variable speed limit signs - used for varying the posted speed limits within work zones and in emergencies. Portable VMS: movable "electronic VMS". A portable VMS has much the same characteristics as a fixed electronic VMS, but can be moved from location to location as the need dictates. == Usage == Early models required an operator to be physically present when programming a message, whereas newer models may be reprogrammed remotely via a wired or wireless network or cellphone connection. A complete message on a panel generally includes a problem statement indicating incident, roadwork, stalled vehicle etc.; a location statement indicating where the incident is located; an effect statement indicating lane closure, delay, etc. and an action statement giving suggestion what to do traffic conditions ahead. These signs are also used for Amber alert messages, and in some states, Silver and Blue Alert messages. In some places, VMSes are set up with permanent, semi-static displays indicating predicted travel times to important traffic destinations such as major cities or interchanges along the route of a highway. Typical messages provide the following information: Promotional messages about services provided by a road authority during non-critical hours, such as carpooling efforts, travelers' information stations and 5-1-1 lines Crashes, including vehicle spin-out or rollover Road Works Incidents affecting normal traffic flow in a lane or on shoulders Non-recurring congestion, often a residual effect of cleared crash Closures of an entire road, e.g. over a mountain pass in winter. Exit ramp closures Debris on roadway Vehicle fires Wildfires Short-term maintenance or construction lasting less than three days Pavement failure alerts AMBER, Silver, and Blue Alerts, as well as weather warnings via the warning infrastructure of NOAA Weather Radio's SAME system Travel times Variable speed limits Car park occupancy levels speed sign, for recommending a speed to approach the next traffic light in its green phase. The information comes from a variety of traffic monitoring and surveillance systems. It is expected that by providing real-time information on special events on the oncoming road, VMS can improve motorists' route selection, reduce travel time, mitigate the severity and duration of incidents and improve the performance of the transportation network. === United Kingdom === Do not enter the motorway when the red lamps are flashing in pairs from side to side. On 27 March 1972, the first motorway computer-controlled warning lights in the UK, with 59 miles on the M6 from Broughton, Lancashire to Barthomley, on the Cheshire boundary, and 26 miles on the M62 east of Whitefield, was switched on by Michael Heseltine and Charles Legh Shuldham Cornwall-Legh, 5th Baron Grey of Codnor at the headquarters of Cheshire Constabulary on Nuns Road. It was centred at a police computer centre at Westhoughton, that connected to police stations in Preston and Chester. The Chester site was soon be connected to the M53 and M57. Four other regional computer centres would be opened at Perry Barr near the M6, Scratchwood near the M1, at Hook near the M3, and at Almondsbury near the M4. Most British motorways would be covered by 1975. The system was designed by GEC and had taken five years to design. == Safety messages for drivers == Increasingly, signs have been used to remind drivers to buckle seat belts ("Click It or Ticket"), obey the speed limit, and stay off the road if impaired ("Drive sober or get pulled over"). In a federal study, a slight majority of drivers reported that public safety messages on dynamic message signs impacted their driving behaviors. The Ohio Department of Transportation began using humorous dynamic message signs in 2015, perplexing some drivers. Examples of humorous signs seen in New Jersey, Arizona, Texas, Pennsylvania, Delaware, Iowa, New York, Minnesota and Ohio include: "Hold on to your butts. Help prevent forest fires." "We'll be blunt. Don't drive high." "Visiting in-laws? Slow down, get there late." "Only sparklers should be lit." and “Don’t drive Star Spangled hammered." (for Fourth of July) "Hocus pocus – drive with focus." and "Slow down in work zones - my mummy works here." (f
WebAR
WebAR, previously known as the Augmented Web, is a web technology that allows for augmented reality functionality within a web browser. It is a combination of HTML, Web Audio, WebGL, and WebRTC. From 2020s more known as web-based Augmented Reality or WebAR, which is about the use of augmented reality elements in browsers. It was the focus of a Birds of a Feather meeting at ISMAR2012 and is now the focus of the W3C Augmented Web Community Group. == Features == Browser augmented reality for smartphones has a number of features that distinguish it from similar content in special apps. No special applications are needed for Web AR. A regular browser is enough. And it can run to a certain extent on most browsers. It is easy to set up marketing analytics. By connecting the website to services that collect statistics, it is convenient to receive geographic coordinates, demographic characteristics and other information about users. Ability to add a CTA button. It is extremely important for marketing websites to place it so that the user can add contact information or place an order after considering the offer. Rich content. Browser augmented reality for tablets and smartphones supports 2D and 3D graphics, animation and other formats. Image marker tracking. If a QR code is selected as an activator for an AR element or just a picture on a flat surface, the device can easily read it. Various activation ways. Web AR can be marker and markerless, attached to geolocation, it can also be hidden in a direct link. Game content. Even simple games with simple mechanics, transferred into augmented reality, can delight the website visitor. Cross-platform. You can view content that complements our usual reality using any modern smartphone model. == Limitations == Performance is simply better on an app, where there's capacity for more memory and programs are executed in native code therefore it provides better visuals, better animations and better interactivity than in WebAR experience. A web page can only have access to certain parts of the device you're using, whereas a native app can access all of a device's capabilities. Meaning if you want the convenience of WebAR, you need to be thinking of simple but effective experiences instead. Compatibility. Not every mobile device has the required HW for AR performance. == Implementation == Browser support is evolving quickly and can best be monitored using services like Can I Use. Since this is a web application, there are platforms that support the creation of WebAR that are similar to normal web development platforms. Something which enables the creation of 3D assets and environments using a web framework that looks similar to HTML. Applications (like for example – A-Frame) are supported by 8th Wall, which is by the end of 2021 the leading SLAM tracking SDK for WebAR on the market. WebAR is currently limited mostly by the browser – so how much the technology will develop rather depends on what the big players like Google and Apple develop. For iOS device users, Apple developed AR Quick Look, an extension that enables users to use ARKit on the web. For Android devices your browser should support WebXR, an API that allows users to view AR/VR content without installing extra plugins or software, and have ARCore installed. There are many tools and frameworks that help developers in expanding the immersive web with WebAR. For example, AR.js is an open-source library for Augmented Reality on the Web for improved WebAR performance on smartphones that includes marker-based technology (simplified QR-codes) and location-based AR. Apple at the WWDC Conference 2018, announced that it has developed a new file format, working together with Pixar, called USDZ Universal. This file will allow developers to create 3d models for augmented reality. USDZ format was created by Apple together with Pixar Animation Studio and allowed developers to create 3D models for AR. == Industries == Where WebAR can be used from virtual guides, which can help students navigate through campus to virtual film posters: E-commerce and Advertising. Education. Entertainment. Business. Fashion. == Examples == Promotion of Spider-Man: Into the Spider-Verse for which 8th Wall developed the AR platform that made this interactive WebAR promoting the Sony animated smash hit. Everyone can invite teenage Spiderman/Miles Morales into their homes for some one-on-one interaction, take pictures and share the experience with friends. Sony Pictures included the QR code to launch this WebAR site in print promotions for the movie. Also in 2017 the advertising of Jumanji: The Next Level gave us the world's first WebAR activation with usage of Amazon Lex to power voice interaction (the same tool that powers Amazon Alexa), the experience sends users on a wild 3D adventure into the world of Jumanji! This was a collaboration between Sony Pictures and Trigger - The Mixed Reality Agency. The WebAR technology is powered by 8th Wall. And you can check it via the link to the official YouTube recording of the experience. RPR & Microsoft's Holographic Retail Platform, where Web AR brings a new twist to online shopping by allowing users to interact with 3D holographic images of models right from their smartphones' browsers. This experience is designed to increase buyer confidence and reduce clothing returns, which are two of the greatest challenges to purchasing clothing online. Digital Porsche Brand Academy was developed by the Team of svarmony Technologies GmbH and it is the first-to-market training tool that uses augmented reality to provide Porsche employees an immersive experience learning about the company's history and values. The star of this WebAR experience is an animated avatar that serves as a tour guide for Porsche's past, present, and future. Employees can explore realistically animated Porsche-locations, take a ride in a virtual Porsche, help assemble a car, and test Porsche knowledge via a quiz. The Digital Porsche Brand Academy is a great starter kit for employees to establish a relationship with the brand and align with the company's plans. == Future == By freeing smartphone users from having to install numerous apps, WebAR can make Augmented Reality far more accessible for them and more beneficial for business. The further development of the WebAR can be accelerated by the widespread social acceptance of the headsets that can give the whole other level of AR experience. This means instant access to the information when the contextually relevant content is appearing as the person's real background is changing.
AI effect
The AI effect is a phenomenon in which advances in artificial intelligence lead to a redefinition of what is considered intelligence, such that capabilities achieved by AI systems are no longer regarded as examples of "real" intelligence. The concept has been used to describe both a cognitive tendency and a sociotechnical pattern, in which successful AI techniques are reclassified as routine computation or absorbed into other domains. Historian Pamela McCorduck described this as a recurring feature of AI research, noting in her 2004 book Machines Who Think that once a problem is solved, it is no longer considered evidence of intelligence. Researcher Rodney Brooks similarly observed in 2002 that once systems are understood, they are often regarded as "just computation". == Definition == The AI effect refers to a shift in how intelligence is defined as machines acquire new capabilities. Tasks such as playing chess, recognizing speech, or interpreting images were historically considered indicators of intelligence, but after successful automation they are often reclassified as routine computation. McCorduck described this as an "odd paradox", in which successful AI systems are assimilated into other domains, leaving AI researchers to focus on unsolved problems. The phenomenon is often interpreted as an instance of moving the goalposts. A commonly cited formulation is Tesler's theorem, often expressed as "AI is whatever hasn't been done yet". When problems are not fully formalised, they may be described using models involving human computation, such as human-assisted Turing machines. == Historical examples == === Game playing === Early AI systems capable of playing games such as checkers and chess were initially regarded as demonstrations of machine intelligence. As these systems improved and became better understood, their achievements were often reinterpreted as examples of computation rather than intelligence. The victory of IBM's Deep Blue over Garry Kasparov in 1997 is a frequently cited example. Critics argued that the system relied on brute-force methods rather than genuine understanding. === Pattern recognition === Technologies such as optical character recognition and speech recognition were once considered core problems in artificial intelligence. As these systems became reliable and widely deployed, they were increasingly treated as standard engineering solutions. === Integration into applications === Many techniques originally developed within AI research have been incorporated into broader technological systems, including marketing, automation, and software applications. Michael Swaine reported in 2007 that AI advances are often presented as developments in other fields. Marvin Minsky observed that successful AI innovations often evolve into separate disciplines. Nick Bostrom noted in 2006 that widely adopted technologies are often no longer labeled as AI. == Contemporary discussion == The AI effect continues to be discussed in the context of recent advances in machine learning, particularly large language models and other generative AI systems. As these systems have become more widely used, some researchers and commentators have noted that their capabilities are frequently described as statistical or mechanical once understood, rather than as intelligence. A 2016 survey of artificial intelligence also noted that AI systems are increasingly embedded in everyday applications, reinforcing earlier observations that successful AI technologies tend to become normalized and no longer identified as AI. At the same time, the widespread commercial use of artificial intelligence has led to greater visibility of the field, contrasting with earlier periods in which AI techniques were often present but unacknowledged. == Interpretations == === Cognitive bias === Some authors describe the AI effect as a cognitive bias in which expectations of intelligence shift as machines achieve new capabilities. === Sociotechnical perspective === Another interpretation emphasizes how technologies are reclassified over time as they become widespread and commercially successful. === Philosophical debate === Some philosophers argue that reclassification reflects genuine conceptual distinctions rather than bias. == Historical context == During periods such as the AI winter, researchers sometimes avoided the term "artificial intelligence" due to negative perceptions. In the 21st century, however, the term "AI" has become widely used in public discourse and marketing. == Broader implications == The AI effect has been linked to broader questions about human uniqueness and the nature of intelligence. Michael Kearns suggested that people may seek to preserve a special role for humans. Similar patterns have been observed in studies of animal cognition. Herbert A. Simon noted that artificial intelligence can provoke strong emotional reactions.
Digital content
Digital content is any content that exists in the form of digital data. Digital content is stored on digital media or analog storage in specific formats. Forms of digital content include information that is digitally broadcast, streamed, or contained in computer files. Viewed narrowly, digital content includes popular media types, while a broader approach considers any type of digital information (e. g. digitally updated weather forecasts, GPS maps, and so on) as digital content. Digital content has increased as more households have accessed the Internet. Expanded access has made it easier for people to receive their news and watch TV online, challenging the popularity of traditional platforms. Increased access to the Internet has also led to the mass publication of digital content through individuals in the form of eBooks, blog posts, and even Facebook posts. == History == At the beginning of the Digital Revolution, computers facilitated the discovery, retrieval, and creation of new information in every field of human knowledge. As information became increasingly more accessible, the Digital Revolution also facilitated the creation of digital content. Despite an evolution to digital technology, which occurred somewhere between the late 1970s, distribution of digital content did not begin until the late 1990s with the rise in popularity of the Internet. In the past, digital content was primarily distributed through computers and the Internet. Methods of distribution are rapidly changing as the Digital Revolution brings new channels, such as mobile apps and eBooks. These new technologies will create challenges for content creators, as they determine the best channel to bring content to their consumers. Despite the benefits, new technologies have created new intellectual property issues. Users can easily share, modify, and redistribute content outside of the creator's control. While new technologies have made digital content available to large audiences, managing copyright and limiting content movement will continue to be an issue that digital content creators face in the future. == Types of digital content == Examples include: Video – Types of video content include home videos, music videos, TV shows, and movies. Many of these can be viewed on websites such as YouTube, Hulu, Paramount+, Disney+, HBO Max, and so on, in which people and companies alike can post content. However, many movies and television shows are not available for free legally, but rather can be purchased from sites such as iTunes and Amazon. Audio – Music is the most common form of audio. Spotify has emerged as a popular way for people to listen to music either over the Internet or from their computer desktop. Digital content in the form of music is also available through Pandora and last.fm, both of which allow listeners to listen to music online for no charge. Images – Photo and image sharing is another example of digital content. Popular sites used for this type of digital content includes Imgur, where people share self-created pictures, Flickr, where people share their photo albums, and DeviantArt, where people share their artwork. Popular apps that are used for images include Instagram and Snapchat. Visual Stories - Stories are a new type of digital content that got introduced by Snapchat. Since then, stories as a format has been introduced in a couple of other platforms such as Facebook and Linkedin. In 2018, Google introduced their AMP Stories, which provides content publishers with a mobile-focused format for delivering news and information as visually rich, tap-through stories. Text - Type of digital content which is available in text or written format. Blog websites which store data in form of textual format. === Paid digital content === In order to have access to more premium digital goods, consumers usually have to pay an upfront charge for digital content, or a subscription based fee. Video – Many licensed videos, such as movies and television shows, require money in order to be viewed or downloaded. Popular services used by many include streaming giant Netflix and Amazon's streaming service, as well as recent notice put forth by the online video platform YouTube. Audio – While songs can be streamed for free, generally in order to download most licensed music, consumers need to purchase songs from web stores, such as the popular iTunes. However, Spotify Premium is emerging as a new model for purchasing digital content on the web: consumers pay a monthly fee to unlimited streaming and downloading from Spotify's music library. According to a report done by IHS Inc. in 2013, the global consumer spending on digital content grew to over $57 billion in 2013, which was up almost 30% from $44 billion in 2012. In past years, the US has always been a leader in consumer expenditure on digital content, but as of 2013, many countries have emerged with great consumer expenditure. South Korea's overall digital spend per capita is now greater than the US. ==== Consolidation ==== According to research firm Ampere Analysis, in 2024, a small group of six media conglomerates; Disney, Comcast, Google, Warner Bros. Discovery, Netflix, and Paramount Global—are poised to dominate the global content market. These companies are projected to account for 51% of all global spending on content, a significant increase from 47% in 2020. Disney, in particular, is a major player, with an estimated $35.8 billion investment in television and film content, representing 14% of global spending. This significant increase, fueled by Disney's full ownership of Hulu, highlights the company's strategic focus on streaming services. A substantial portion of the projected $126 billion global content spending is allocated to streaming platforms. === Non-purchasable digital content === Not all digital content is purchasable, and is simply anything published digitally. This would include: News – in recent years newspapers have attempted to expand their readership by creating access to their newspapers digitally. As of 2012, 39% of readers learned about news from online formats, making news a prevalent form of digital content. Advertisements – as media consumers increasingly use digital formats to watch TV, check the weather, and search for content, advertisements have shifted to digital forms to keep up with their viewership. Advertisements are now being made digitally and placed on sites ranging from Facebook to YouTube. Question and Answer sites – these sites are a type of Internet forum where people can post questions they want answered, or provide responses to previous inquiries. With millions of questions posted each day, anyone has the ability to create content on these sites, so the information provided may not be 100% reliable or accurate. Popular sites include Yahoo! Answers, WikiAnswers and Quora. Web mapping – sites such as MapQuest and Google Maps provide users with map content. These sites give people the ability to quickly look up the location of a landmark and create routes to a destination. Online maps are a form of free content provided by companies such as Google and AOL, serving as much more efficient alternatives to the traditional Thomas Guide. == Business implications == === Digital companies === Digital content businesses can include news, information, and entertainment distributed over the Internet and consumed digitally by both consumers and businesses. Based on revenue, the leading digital businesses are ranked Google, China Mobile, Bloomberg, Reed Elsevier, and Apple. The 50 companies with the highest revenue are split between those offering free and paid digital content, but these top 50 companies combined generate revenue of $150 billion. === Educational opportunities === Programs such as CUNY's Macaulay Honors College in their New Media Lab, run by industry professional Robert Small, is set up to train and introduce students to the various disciplines within the digital content industry. The goal is to offer information and access to professional work opportunities. They also explore within an incubator how to create businesses and start ups within the world of digital content. There are many educational events in support of choosing digital content as a career. === Government support === The Irish government adopted a "Strategy for the Digital Content Industry in Ireland" in 2002.