The value – and dangers – of volunteer editors

Our culture is undergoing a rapid “wikification,” where nearly every form of content imaginable can now be edited and reconfigured by members of a community. Supported by technological innovations that make remote editing easier to track and implement, legions of volunteer editors have emerged to help authenticate, structure and moderate the vast quantity of content available to the public. Indeed, Wikipedia benefits from the volunteer services of over 80,000 editors who comb through the more than 38 million articles hosted on the site, verifying data and flagging errors. These editors are unpaid, largely anonymous and not required to have any kind of formal training.

Why would people donate countless hours to manage content to little or no acclaim? And a deeper question: Are these volunteer editors a boon for content managers or a danger?

“These editors are unpaid, anonymous and not required to have any kind of formal training.”

Motivations and psychology 
From an economic perspective, the decision to employ volunteer editors is a no-brainer. If an organization is able to obtain free editing services, it can redirect resources to other capital-intensive projects. There is even a qualitative argument to be made based on the “crowdsource” aspect of community editing – that, by opening up editing privileges to the community at large, the ability to quickly verify and validate date on a grand scale is possibly without having to wrestle with outside interests and intellectual gatekeepers.

To understand the value of volunteer editing, it helps to start by examining the motivations of a person who engages in it. Looking at the question of why people volunteer to edit for the site, the Behavioral Science and Policy Association recently conducted an experiment to see what factors motivated community editors working within Wikipedia. BSPA randomly assigned certain editors within the German language Wikipedia community a “Edelweiss with Star” badge, which could be displayed prominently on a user’s profile or otherwise hidden. Members of this badged community exhibited higher rates of editor retention – over 20 percent after one month and 14 percent after two months.

While this would lead some to assume that public recognition could boost editor retention, the experiment found that only about 6 percent of the badge recipients opted to display the badge publicly – implying that recognition with the community may not be a strong driver of retention. This led study author Jana Gallus, a postdoctoral fellow in the Behavioral Insights Group at Harvard, to speculate that each editor’s feeling of belonging to a community may drive people to volunteer in such high numbers.

Edits attract edits
Then there are the dynamics of the community/volunteer editing process itself. Stephan Seiler, an economist and associate professor of marketing at Stanford Graduate School of Business, and Aleksi Aaltonen, an assistant professor of information systems at Warwick Business School, studied the editing patterns of nearly 1,310 articles over eight years. Articles that were community edited, they found, tended to be edited frequently, attracting new edits and editors like magnets. This they dubbed the “cumulative growth effect,” which basically means a snowballing of content editing that occurs once a prepopulated article attracts the attention of editors – which in turn begets more edits.

“Simply putting [an article up] up and hoping that people will contribute won’t work,” Seiler told Stanford Business. “But any action that increases content can trigger further contributions.”

“Inaccuracies can become increasingly hard to track and invalidate.”

The dangers of volunteer editing
It’s not clear that the “cumulative growth effect” is necessarily a good thing. One of the much lamented aspects of Wikipedia is that it can be edited – and reedited – at the whim of almost any registered user. This has led to an unknown number of hoaxes, frauds and vandalized pages – inaccuracies that can become increasingly hard to track and invalidate if they are used as sourcing for journalism or academia.

This is the essential danger of volunteer editing: without requiring specific qualifications – and the ability to meaningfully penalize or incentivize edit quality – inaccuracies are likely. Even in its most benign occurrence, a simple error or misunderstanding can taint the validity of a piece of content. At worst, you can get intentional and malicious obfuscation of data. This has kept many content management organizations from adopting the full-scale community editing capabilities pioneered by Wikipedia.

Copyright and trademark in content management systems

 

Given that much of content creation is oriented around the construction of instructional or technical documentation, the issue of copyright and trademark is often not considered when designers and authors are working with a content management platform. Yet the ubiquity of existing content and data, as well as changing regulatory guidance and commercial interest in copyright holders has made this an important consideration.

“Even within technical writing, an eye for copyright must be observed.”

Even within technical writing, an eye for rights must be observed. In laying out his guiding principles for an effective content marketing strategy, Columnist Robert Norris writes in The Content Wrangler that organizations should make sure that “copyright is respected, intellectual property is protected and digital record retention is prescribed.”

Specifically, he cautions that an enterprise publishing initiative must make “a commitment to integrity and record-keeping” by archiving source material. Still, this in and of itself can become problematic if the XML content management platform cannot properly handle copyrighted or trademarked material. If this material is treated the same as public domain materials or common knowledge in an automated curation or authorship process, copyright infringement can occur and be disseminated without being flagged ahead of time.

This underscores the importance of creating “fair use,” permission and citation protocols in your content authoring processes, and ensuring that the XML CMS supports these protocols. By flagging copyrighted content and adding hypertext data about the copyright holder, when building a new piece of content, sourcing copyrighted or trademarked content can be made subject to tiered rules, prompting authors to reach out to the copyright holder for approval or automatically adding copyright notices to documents.

Furthermore, the more sophisticated XML content management platforms allow writers to repurpose data contained within copyrighted content and build content from there. The legal guidance on copyright holds that information – unless a trade secret or somehow proprietary – is not protected; copyright protection applies to the way the information is expressed. This makes component-based authoring paradigms like DITA useful for coding content from a particular source and identifying which pieces of information are subject to proprietary protection.

Approaching sourcing from this angle, however, requires a significant amount of capability in the content management platform; hence many CMSs (particularly within education) opt more for linking rather than importing copyrighted content wholesale.  When linking is not an option, though, importing copyrighted content into an XML CMS like Astoria requires proper labeling and role-based access designations to avoid the legal hazards surrounding access to copyrighted content and protection against exposure or misuse by parties that are not authorized to work with the material.

Overcoming the issue of scaling

Developing any high-level content management architecture in the age of big data has uncovered hidden challenges, ones that engineers and program designers never could have anticipated in previous years. While our computer storage and processing capacities continue to expand, the sheer volume of data being produced has led to many computing issues relating to scale.

The von Neumann bottleneck
Even the most sophisticated CMS available on the market cannot hope to handle every single piece of content being churned out. For standard personal computers, this leads to what experts have dubbed the von Neumann bottleneck. As Astoria Software CEO Michael Rosinski recently discussed with The Content Wrangler's Scott Abel, this refers to a common latency issue occurring when discrete processing tasks are completed linearly, one at a time.

The von Neumann bottleneck is easy to understand.  Even though processors have increased in speed and computer memory has increased in density, data transfer speeds between the CPU and RAM have not increased.  This means that even the most powerful CPU spends as much as 75% of its time waiting for data to load from RAM.  CPU designer Jonathan Kang goes even further, claiming that this architecture model results in "wasteful" transfers and implying that the data need not be retrieved from RAM in the first place.

"To scale effectively, implementing predictive algorithms is necessary."

Predictive and intelligent
The solution, as Mr. Kang sees it, is to associate data with the instructions for its use.  In that way, as the instructions move into the CPU, the data pertaining to those instructions moves into the CPU cache, or is accessible through an alternate addressing channel designed specifically for data.

Another approach, and one more amenable to large sets of data, is to preprocess the data as it is ingested.  We recognize that not all content will be of high value in a particular set – most of it may in fact be of relatively low value – so the ability to approach content management with a sense of data relevance allows programmers to apply CPU and RAM resources to the data with the highest value.

This is at the core of intelligent computing – and intelligent content. Since existing hardware architectures contain limits a computer's ability to transfer data, there is much to be gained by creating data ingestion programs that are able to mimic a human's ability to determine data relevance and recognize content insights – techniques that overcome latency by quickly and efficiently pinpointing only the data we need.

"Every time a piece of intelligent content is processed, the machine 'learns.'"

Content versus computing
Fully intelligent computing (essentially a form of AI) remains elusive, but within the realm of content management, great strides are being made every day. One of the biggest innovations is the changing of approach from placing the full burden on computing to integrating "intelligent" features into the content itself. With the more complicated architecture content languages like XML and DITA, we can add extensive semantic context, aiding the CMS by tagging and flagging data relevance. Every time a piece of intelligent content is processed, the machine "learns" patterns and uses these patterns help deal with issues of scale.

Over time, the combination of machine learning and structured, intelligent content will lead to faster, more accurate decision-making and the ability to keep up with a constant influx of new data. It can connect multiple data sets, recognizing common metadata tags across platforms, devices and channels and making data aggregation easier. This will have an immense impact on all industries, from retail to customer service to education to medicine.

Segmentation as a key to personalized content delivery, part 2

Welcome back to the second part of our series on ways to segment audiences to ensure a customized, pinpointed content experience for each user. Last time, we reviewed the various considerations and rules that govern segmentation. In this installment, we describe an implementation plan for effective segmentation and incorporating those rules into content classification.

Capturing segments and delivering content
The first task to establishing effective user-facing content is to identify your audience, both intended and actual.

"Develop your audience baseline; i.e., your assumptions about your audience."

Early on, develop a clear strategy built around an ideal user profile, broken down demographically, behaviorally and psychographically. Prior to content delivery, this will act as your audience baseline, i.e. who you think your audience is. Do not treat this ideal user profile as gospel; you may find – once you are up and running delivering content – that your actual user is very different from what you envisioned.

Having set your audience baseline, tag your content according to the anticipated values and interests of each segment demographic. Ideally, this is built off extensive market research or experiential knowledge of these particular users. Again, nothing about this initial tagging should be considered set in stone, since even the most knowledgeable industry experts may have their initial findings challenged when expanding out to the broader audience. In fact, your content management system, such as the Astoria Portal, should allow you to build in rule overrides or retag content that has been published already.

From there comes capturing segments. There are a variety of methods to accomplish this task, from market research to advance data aggregation and analytic tools, but one of the most effective methods is simple self-selection. Make the interface intuitive enough for users to identify their segments, and have this selection drive their user experience.

Tagging and retagging
An example of this in action could be a website gateway for educational materials where the landing page prompts visitors to identify themselves as teachers, administrators, parents or students. After clicking the pertinent segment, the user is then sent to a customized portal, with targeted content delivered directly to them. Alternatively, a site may have a mailing list signup where users are prompted to input demographic and interest data (age, sex, location, how often they buy certain products, how much they spend), which can then be used to automatically deliver content to each email subscriber based on their personal preferences.

"Are unexpected content requests coming in?"

Once users have started interacting with your content, the true test of your segmentation rules and category-level metadata begins. This can be determined by looking at user behaviors: Are users spending more or less time with some content compared to others? Are unexpected content requests coming in? Regular auditing of your metadata tagging may help pinpoint misclassifications, evolving user needs or even create more granular tagging rules.

Keep segments clean and segregated
It is critical that the user experience be as intuitive and streamlined as possible. When it comes to delivering customized content, start with a common set that works across all the different user experiences, sharing some of the same essential data and supplementing and restructuring the experience based on the user persona. Avoid prompts that could lead users away from the central content hub and instead try and have content flow inward. A good technique is a prompt like "Read more", which can expand content on the current page with supplementary materials.

By having audiences self-identify based on their content preferences, you can match metadata tagged content while measuring results versus expectations. This can offer vital insight for content managers about how effective tagging systems – and the content itself – serves the intended audience segment.

Segmentation as a key to personalized content delivery, part 1

When it comes to delivering personalized, localized and – most importantly – relevant content to audiences, segmentation is a key concept. Segmentation, in this context, does not refer to the division of text into translatable chunks.  Instead, it refers to the classification of content consumers according specific parameters.

There is a compelling business need for incorporating segmentation into an information architecture: helping customers make purchase decisions about the products and services described in your content. The underlying problem is the evolutionary expansion of technology; namely, as storage capacity expands and content management capabilities grow more sophisticated, the volume of data under active management also expands. Yet, brands, companies and other content providers must continue to deliver only the most relevant content to their customers while screening out irrelevant data that can otherwise disable crucial decision-making when it comes to making purchases.

The solution to this problem has two parts. The first action, discussed in the following paragraphs, is to develop effective, defensible rules for segregating the people who read your content. The second part, which will be discussed separately, is to incorporate those rules into the way you classify your content.

"The first step is to building segmentation is to develop audience personas."

So how do you develop appropriate segmentation rules? The first step is to build audience personas, defining the qualities and interests that will route your audience to different pieces of content. Building these simply from end-user IP addresses, however, is tilting at windmills. A better segmentation strategy focuses on a few primary areas where audiences offer distinguishing characteristics and then sorting these characteristics into their respective content channels. Here are candidate primary identifiers for segmenting your audience.

Geographic
While it's asking the impossible to build audience personas solely from IP addresses, it is nonetheless true that IP addresses offer some meaningful guidance to the task. For example, you can know whether or not to deliver translated or localized versions of your content.  You can pinpoint cultural signifiers and traditions that may shape how your audience interacts with content. Then there's the fact that IP addresses help you identify key geographic zones of influence, be they broad measures such as a continent or a country, or more precise identifiers such as a region, a county or ZIP code. While our increasingly interconnected world has broken down the barriers that once defined a geography, different areas can still drive audience behaviors and thought in a way that requires segmenting.

Demographic
From the "where?" of geographic identifiers, demography identifies the "who?" that makes up your audience. Demographics can take on a nearly infinite array of attributes, from gender to age to national origin to economic status and income. Probably the most immediately relevant is occupation, since the services being offered can be specific to a certain audience within a single company (for example: HR supervisors versus regional managers).

Demography identifies the "who?" of your audience.

Behavioral
Behavioral attributes are simply the answer to the question, "What actions does this audience segment regularly perform?" This method examines patterns of behavior: where people shop, what they buy, what kind of web pages they look at and for how long.

Psychographic
Psychographic segmentation is one of the more nuanced approaches to audience segmenting since it takes data from geographic, demographic attributes, and behavior sources to synthesize a psychological profile. This profile, though, is less about identifying patterns in what people do and more about identifying what and how they think. Hence, a profile subjected to psychographic segmentation focuses on the following attributes:

  • Lifestyle and personality. Beyond their behavior, audiences identify themselves in accordance with the aspects that have the most meaning in their lives. This can be a self-identified interest derived from behavior but distinct from it. A person may identify with and fit the profile of a "Harley-Davidson bike owner" even without purchasing a motorcycle. A sustained interest in the culture and ephemera related to Harley-Davidson ownership is enough to accurately capture this audience segment and deliver customized content. 
  • Values, attitudes and opinions. Values, attitudes and opinions provide the framework of thought and perspective, which drives an emotional response to stimuli.
  • Social class. Class consciousness plays a big role in psychographic identification. Class differs from lifestyle in that "class" describes an inherited set of rules (acquired through family or peer-group interactions) governing where people exist and how they relate to others in various classes, whereas "lifestyle" describes a set of chosen interests. A prime example is the upper-class young lady looking for information on handbags who is driven by the luxury standards of her social circle, as compared to a middle-class young lady looking for information on inexpensive, rugged alternatives. 

Next time, we will explore the ways to most effectively and accurately identify audience segments and funnel them into your content.

Translation versus localization: creating globalized content

In an interconnected world, your content has value far beyond your backyard – so long as people can understand it. As part of the globalized content market, design teams are faced with a fundamental choice: should content strategy prioritize translation, localization or some combination of the two?

Reading versus comprehending
The first obstacle in developing the most effective strategy is that content marketers often don't recognize the distinctions between the two approaches. The terms "translation" and "localization" are often used interchangeably. 

"Your content has value far beyond your backyard."

The simplest way to understand the difference between translation and localization is to think of the underlying values they serve. Translation is a very literal, data-driven process: it takes data from one locale and substitutes its equivalent value in another locale. This means that on a basic level, the document is being reformatted to be read by a foreign audience.

For enterprises operating outside of their domestic market, bringing native content to foreign readers represents a challenge – one often met with a ham-fisted "throw it in a translator" approach. But as anyone who has used an online translation service may have noticed, a substitution-style translation of text or other content doesn't always result in something that makes sense. Even technical documents, driven and quantified by empirical data, may end up virtually incomprehensible – although technically readable – after a such a translation.

Crossing the cultural barrier
Karl Montevirgen, writing in The Content Wrangler, explains that translation is concerned with bridging the language barrier, while localization is about crossing the cultural barrier. As with prose, a certain vernacular expression or linguistic shorthand in technical material written for one culture may not carry over into another culture. Even in the hands of a trained bilingual and without a simplistic word-by-word translation, content that speaks to readers in different cultures with equal fidelity can be elusive.

This is where the world of dynamic content writing has a unique edge when it comes to translation. Depending on the sophistication of the content management and editing system, the ability to divide content into hypertext components makes translation more than simply substituting words; it allows for complex reconstitution of content into another language.

"With localization comes added costs – both monetary and time."

The value and cost of localization

This is where localization can edge out translation as a strategy to market content. By creating customized content with a culture's native tongue, you can ensure that the content speaks directly in the language of your audience while taking on the cadence and cultural mores of that demographic. This can have significant value when it comes to avoiding any miscommunication or snafus that may arise by awkward translation.

However, with localization comes added costs – both monetary and time. Localization requires native speakers and contributors, which will be able to communicate in any specific target language but may not be experts or otherwise familiar with the subject matter of the content. Alternatively, locally created content may be functionally indecipherable to the home enterprise, making fact-checking and editing impossible.

In the end, an enterprise looking to spread its content globally employs some mix of translation and localization to achieve the optimal combination of cost, schedule, and meaningful outreach.

How will online archiving influence content management?

The advent of Internet archiving has changed the way we think about media and content.  The continuum of information has flattened, unchained as it is from physical form, so that as soon as content is published, it can be cataloged, reused and repurposed at any time.

"As soon as content is published, it can be cataloged, reused and repurposed."

At the forefront of this revolution are websites like the Internet Archive. The site has amassed approximately 25 petabytes of data — a repository of digitized media including books, films, TV clips, websites, software, music and audio files, photos, games, maps, court/legal documents — all made freely available. As part of its "Wayback Machine" project, the Internet Archive offers the Archive-It tool, which has thus far saved historical copies of 484 billion retired and indexed web pages and which allows users to "[c]apture a web page as it appears now for use as a trusted citation in the future." The operators of the site liken the archive to the fabled Library of Alexandra – a repository of human knowledge and culture, supposedly lost in antiquity. 

"We believe it's crucial to provide free access to information. Our society evolves because of information, and everything we learn or invent or create is built upon the work of others," Alexis Rossi, Internet Archive's director of Media and Access, told The Content Wrangler. "In a digital age, when everything is expected to be online, we need to make sure the best resources are available. The human race has centuries of valuable information stored in physical libraries and personal collections, but we need to ensure that all of it is online in some form."

The challenge of cataloging
While maintaining the massive archive — according to Rossi, the site tops 50 petabytes due to built-in replication and redundancy — is a feat of engineering itself, the true challenge is in cataloging and maximizing accessibility. This is where the world of content management and archiving begin to intersect. By combing through the archives and breaking its content into hyperlinked components (similar to the way one constructs content in DITA), this can render content much more discoverable and thus able to be repurposed for new content.

This represents a distinct evolutionary – and revolutionary – shift in the way that we approach content, primarily in terms of scope. Whereas traditional authors might have been limited to accessing historical materials, modern authors are now theoretically unbound because all recorded and cataloged media and content are available at their fingertips. The fundamental question for authors and curators changes from "Does this content exist for citation?" to "Can I find the content?"

"Authors are now unbound by the traditional constraints of archiving."

The great equalizer: Free
Tied into this increased availability is the fact that the content made available by Internet Archive and similar sites is totally free. This access model, in its own way, has become an equalizer of sorts, homogenizing the "Can I find it?" question to an egalitarian take on human knowledge. The free component is an ideological cornerstone of the Internet Archive and its contributors, which includes Jessamyn West, a library consultant and community liaison for the Open Library project.

"We make it available for free, and that's especially important to the underprivileged and to people in other countries who may not have free access to information," West said to The Content Wrangler. "This kind of access has great value, because knowledge is power."

This, however, may be a simplified take on the true value of archiving. While not every site may provide meaningful — or accurate — information, experts like John Wiggins, director of Library Services and Quality Improvement at Drexel University, claim that content creators can still benefit from the historical aspect of an archive, allowing them a glimpse into the way cultural forces have shaped and guided content throughout time.

A return to physical content archiving?

In a unique and unexpected twist on the traditional push to digitalization, Hi.co has announced it is shuttering its site, freezing services as of September 2016. What makes the story surprising is that the site's operators, Craig Mod and Chris Palmieri, have written in a Medium post that they will be archiving the site's nearly 2,000,000 words and 14,000 photos onto a microprinted two-by-two-inch nickel plate and sent to various locations all over the world, including a copy ending up in the Library of Congress.

'Medium, not media' 
The plates can only be viewed with a 1,000-power optical microscope and have a lifespan of roughly 10,000 years, resistant to fire, water and salt damage. Mod and Palmieri pointed out that, while they will be paying to maintain a digital, hosted version of the site and a historical copy will be entered into the Internet Archive, the process is designed to embrace a physical footprint over a digital one.

"The process does not produce "data." It is not like a CD," write Mod and Palmieri. "It is not a composition of 0's and 1's representing the information. It is the information itself. The nickel plate is a medium, not media.""

"The nickel plates have a lifespan of roughly 10,000 years."

Repository or crypt?
This take on "time capsule" archiving is nothing new: In their coverage of the Hi.co project, The Atlantic talks about the Crypt of Civilization, a 2,000-square-foot sealed vault initiated by President of Oglethorpe University in Atlanta, Thornwell Jacobs, in 1940. The vault contains about 640,000 pages of text reproduced on microfilm and is designated to be reopened in 8113 C.E.

"Today we can place articles in the crypt and nothing can keep them from being readable a million years from now," remarked Jacobs while planning the Crypt in 1938. This, in a sense, mirrors the optimism of Mod and Palmieri and even alludes to the coming modern era of increasingly inexpensive and simple content archiving. However, only two years later, Jacobs seemed to have taken on a more somber tone in the wake of global war breaking out.

"The world is now engaged in burying our civilization forever," he recorded as part of speech included in the Crypt, "and here in this crypt we leave it to you."

Time capsules 
While these words may seem melodramatic, they retain a certain ring of truth even now: While our archiving and content management capabilities have grown more sophisticated, archives will always remain vulnerable to acts of malice, negligence or simple indifference. The vast digital depositories of information we have aggregated and cataloged could vanish into the ether with the failure of a specific server or be rendered unreadable by future generations accessing it with futuristic technology. In essence, while the idea of a physical archive for media may seem antiquated, it may in fact be a worthwhile investment in preserving content well into the foreseeable future.

New White House initiative aims to bring government into tech age

Marking a distinct transition from the technological missteps of previous years, the White House has announced the formation of the United States Digital Service. Described as a "startup" founded by President Obama, the goal is to partner government with technology providers to create a more intuitive, modern approach to addressing national priorities.

"What if interacting with government services were as easy as ordering a book online?" writes the Executive Office of the President. "The challenges behind HealthCare.gov brought this question to the forefront, changing our government's approach to technology."

"The White House has announced the formation of the United States Digital Service."

Learning from past mistakes
Indeed, this reference to the issues that occurred during the launch of HealthCare.gov is telling. As the first major push to implement public policy via a major technological initiative, the seemingly unending issues hampered the site's overall efficacy and put a serious damper on the optimistic tone of the Obama administration. Rather than attribute the failure to negligence or mismanagement, industry experts like Aziz Gilani saw the site as an example of "too much, too fast."

"The federal government is just like every other enterprise out there," Gilani told CMS Wire. "It's facing a lot of pressure to join the world in Software-as-a-Service (SaaS) transformation, but then be able to release and maintain applications with the shortened sprint times required to support those types of applications."

Enlisting help from the world of tech
Through the USDS, the government aims to avoid the errors of the past by bringing technological infrastructure design in-house. To do this, the startup employs a team of engineers, led by Mikey Dickerson, a former Google engineer who played a key role in salvaging Healthcare.gov. Dickerson has been an outspoken critic of the government's previous efforts – or lack thereof – to embrace technology, saying that the private sector has long since blown past federal agencies in the way they interface with cutting-edge technology.

"First of all, government still calls it 'IT' and 'cyber' which the tech industry does not, and that's a clue right there," Dickerson told Gov Insider. "This issue has become particularly acute and visible to the public in a really painful way. Ten years ago the iPhone didn't exist and now innovations like smart phones, GPS and Uber are deeply intertwined across people's everyday lives – with government looking flat-footed by comparison."

"Different systems designed separately breed translation and communication issues."

Streamlining content design and dissemination
One of the biggest hurdles to government-sponsored technology is creating consistency across every agency. In previous years, the government eschewed a top-down approach to content design and consistency, opting instead to have each agency individually contract out for their technology needs. This led to a fundamental operational roadblock: Design would vary dramatically from agency to agency.

Beyond the aesthetic mismatch and user-experience incongruities stemming from this lack of consistency, disparate systems separately designed bred translation and communication issues. Cross-agency data exchange became difficult, contributing to the infamous delays associated with government agency communications. It also rendered the ability to generate data-rich hypertext effectively impossible.

These are essentially the same problems facing large groups of content creators who operate within the same company but are otherwise completely disjointed in their associations with each other.  Agreeing to a common set of information architecture rules brings these groups into alignment.  Establishing a common data-encoding standard lets them share their information more easily.  Adopting a common set of tooling streamlines the collaboration and the overall productivity of each team.

The USDS is following a similar playbook. Its U.S. Web Design Standards program provides a style guide, mobile-responsive design constraints, and recommended open-source coding tools to create a seamless web standard across all agencies subject to federal oversight. Whether or not the USDS will broaden its scope to include content creation and management systems remains to be seen, but the push towards commonality inspires some optimism within the world of content strategy.

A browserless world via chat apps?

Just when the content market gains parity with full web 2.0 integration, new apps and functionality are shaping the way we manage and distribute content to consumers. An emerging trend: a shift away from open accessibility browsers to proprietary chat apps.

In Facebook's Spring 2016 announcement of expanded functionality in its Messenger app, one of the benefits emphasized by the social media giant was new content publishing capabilities. Facebook invites developers to build bots that use the Messenger Send / Receive API, which now supports, "…not only sending and receiving text, but also images and interactive rich bubbles containing multiple calls-to-action." The company also announced integration of Wit.ai's Bot Engine, which allows for developers to build more "complex" bots around machine-learning algorithms that can process natural language patterns. 

"80 percent of user time is spent on just five applications."

Too much to surf
While it's difficult to speculate as to its full impact, the expansion of chat app functionality may in fact signal that consumers are looking for a more direct way to receive and transmit data by way of content.

"Today, we no longer surf the web because there's too much to surf," writes Chris Moore is Chief Revenue Officer of Nexmo for The Content Wrangler. "Now, the bottomless ocean of information and data at our disposal has arguably become the Internet's biggest weakness. That reality, combined with the rise of smartphones as mainstream consumer devices, has ushered in an app economy where chat apps are fast becoming the new default destination for web-bound consumers."

Moore goes on to say that, according to a recent Forrester report, 80 percent of user time is spent on just five applications, with the closed-system of social media and messaging being the primary places spent. This could effectively mean that chat isn't just the web of tomorrow – it's essentially the web of today. 

An evolutionary essential 
So what does this mean for content managers? Simply, it means that chat- and social integrated-content management tools are a growing necessity. The ability to aggregate content and data, and apply learning algorithms in the forums where the most communication is occurring is the next evolutionary step for the content management and hypertext market. This means, too, that XML content management systems cannot hope to stay relevant in a market where content consumers are looking to bypass browser-oriented portals in favor of direct-from-the-vendor apps driven by user-configured bots.

According to Daniel Nations, a trend expert for About Tech, the "browsers of tomorrow" will likely be each website offering unique, proprietary apps and creating a seamlessly integrated browsing experience.

"I imagine it would be like merging our current browsers, ActiveX, and Java to create something that can be both a mini-operating system and a development platform," speculates Nations.

Mr. Nations may be showing his age, since ActiveX and Java in the browser are falling out of favor for their nearly innumerable security weaknesses.  Nevertheless, his core point is worth noting, "For you and me, it would be like loading up our office application, seamlessly switching between a word processor and a spreadsheet, and just as seamlessly switching to a massively multiplayer online roleplaying game."