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Understanding the Smart Content Technology Landscape

If you have been following recent XML Technologies blog entries, you will notice we have been talking a lot lately about XML Smart Content, what it is and the benefits it can bring to an organization. These include flexible, dynamic assembly for delivery to different audiences, search optimization to improve customer experience, and improvements for distributed collaboration. Great targets to aim for, but you may ask are we ready to pursue these opportunities? It might help to better understand the technology landscape involved in creating and delivering smart content.

The figure below illustrates the content technology landscape for smart content. At the center are fundamental XML technologies for creating modular content, managing it as discrete chunks (with or without a formal content management system), and publishing it in an organized fashion. These are the basic technologies for “one source, one output” applications, sometimes referred to as Single Source Publishing (SSP) systems.

smart technology landscape

The innermost ring contains capabilities that are needed even when using a dedicated word processor or layout tool, including editing, rendering, and some limited content storage capabilities. In the middle ring are the technologies that enable single-sourcing content components for reuse in multiple outputs. They include a more robust content management environment, often with workflow management tools, as well as multi-channel formatting and delivery capabilities and structured editing tools. The outermost ring includes the technologies for smart content applications, which are described below in more detail.

It is good to note that smart content solutions rely on structured editing, component management, and multi-channel delivery as foundational capabilities, augmented with content enrichment, topic component assembly, and social publishing capabilities across a distributed network. Descriptions of the additional capabilities needed for smart content applications follow.

Content Enrichment / Metadata Management: Once a descriptive metadata taxonomy is created or adopted, its use for content enrichment will depend on tools for analyzing and/or applying the metadata. These can be manual dialogs, automated scripts and crawlers, or a combination of approaches. Automated scripts can be created to interrogate the content to determine what it is about and to extract key information for use as metadata. Automated tools are efficient and scalable, but generally do not apply metadata with the same accuracy as manual processes. Manual processes, while ensuring better enrichment, are labor intensive and not scalable for large volumes of content. A combination of manual and automated processes and tools is the most likely approach in a smart content environment. Taxonomies may be extensible over time and can require administrative tools for editorial control and term management.

Component Discovery / Assembly: Once data has been enriched, tools for searching and selecting content based on the enrichment criteria will enable more precise discovery and access. Search mechanisms can use metadata to improve search results compared to full text searching. Information architects and organizers of content can use smart searching to discover what content exists, and what still needs to be developed to proactively manage and curate the content. These same discovery and searching capabilities can be used to automatically create delivery maps and dynamically assemble content organized using them.

Distributed Collaboration / Social Publishing: Componentized information lends itself to a more granular update and maintenance process, enabling several users to simultaneously access topics that may appear in a single deliverable form to reduce schedules. Subject matter experts, both remote and local, may be included in review and content creation processes at key steps. Users of the information may want to “self-organize” the content of greatest interest to them, and even augment or comment upon specific topics. A distributed social publishing capability will enable a broader range of contributors to participate in the creation, review and updating of content in new ways.

Federated Content Management / Access: Smart content solutions can integrate content without duplicating it in multiple places, rather accessing it across the network in the original storage repository. This federated content approach requires the repositories to have integration capabilities to access content stored in other systems, platforms, and environments. A federated system architecture will rely on interoperability standards (such as CMIS), system agnostic expressions of data models (such as XML Schemas), and a robust network infrastructure (such as the Internet).

These capabilities address a broader range of business activity and, therefore, fulfill more business requirements than single-source content solutions. Assessing your ability to implement these capabilities is essential in evaluating your organizations readiness for a smart content solution.

What’s Hot in XML? Workshop on Smart Content Describes Leading-Edge Content Applications

What is hot in XML these days? I have been to a few conferences and meetings, talked with many clients, participated in various research projects, and developed case studies on emerging approaches to XML adoption. DITA (Darwin Information Typing Architecture) is hot. Semantically enriched XML is hot. Both enable some interesting functionality for content delivered via print, on the web, and through mobile delivery channels. These include dynamic assembly of content organized into a variety of forms for custom uses, improved search and discovery of content, content interoperability across platforms, and distributed collaboration in creating and managing content.

On November 30, prior to the Gilbane Conference in Boston, Geoff Bock and I will be holding our 3rd workshop on Smart Content which is how we refer to semantically enriched, modular content (it’s easier to say). In the seminar we will discuss what makes content smart, how it is being developed and deployed in several organizations, and dive into some technical details on DITA and semantic enrichment.  This highly interactive seminar has been well received in prior sessions, and will be updated with our recently completed research findings.  More information on the seminar is available at  http://gilbaneboston.com/10/workshops.html.

By the way, t The research report, entitled Smart Content in the Enterprise, is now available at the research section at Gilbane.com. It (now available from Outsell Inc) includes several interesting case studies from a variety of organizations, and a lot of good information for those considering taking their content to the next level. We encourage you to download it (it is free). I also hope to see you in Boston at the workshop.

How Smart Content Aids Distributed Collaboration

Authoring in a structured text environment has traditionally been done with dedicated structured editors. These tools enable validation and user assisted markup features that help the user create complete and valid content. But these structured editors are somewhat complicated and unusual and require training in their use for the user to become proficient. The learning curve is not very steep but it does exist.

Many organizations have come to see documentation departments as a process bottleneck and try to engage others throughout the enterprise in the content creation and review processes. Engineers and developers can contribute to documentation and have a unique technical perspective. Installation and support personnel are on the front lines and have unique insight into how the product and related documentation is used. Telephone operators not only need the information at their fingertips, but can also augment it with comments and ides that occur while supporting users. Third-party partners and reviewers may also have a unique perspective and role to play in a distributed, collaborative content creation, management, review, and delivery ecosystem.

Our recently completed research on XML Smart Content in the Enterprise indicates that as we strive to move content creation and management out of the documentation department silo, we will also need to consider how the data is encoded and the usefulness of the data model in meeting our expanded business requirements. Smart content is multipurpose content designed with several uses in mind. Smart content is modular to support being assembled in a variety of forms. And smart content is structured content that has been enriched with semantic information to better identify it’s topic and role to aide processing and searching. For these reasons, smart content also improves distributed collaboration. Let me elaborate.

One of the challenges for distributed collaboration is the infrequency of user participation and therefore, unfamiliarity with structured editing tools. It makes sense to simplify the editing process and tools for infrequent users. They can’t always take a refresher course in the editor and it’s features. They may be working remotely, even on a customer site installing equipment or software. These infrequent users need structured editing tools that are designed for them. These collaboration tools need to be intuitive and easy to figure out, easily accessible from just about anywhere, and should be affordable and have flexible licensing to allow a larger number of users to participate in the management of the content. This usually means one of two things: either the editor will be a plug in to another popular word processing system (e.g., MS Word), or it will be accessed though a thin-client browser, like a Wiki editor. In some environments, it is possible that both may be need in addition to traditional structured editing tools. Smart content modularity and enrichment allows flexibility in editing tools and process design. This allows the  use of a variety of editing tools and flexibility in process design, and therefore expanding who can collaborate from throughout the enterprise.

Also, infrequent contributors may not be able to master navigating and operating within a  complex repository and workflow environment either for the same familiarity reasons. Serving up information to a remote collaborator might be enhanced with keywords and other metadata that is designed to optimize searching and access to the content. Even a little metadata can provide a lot of simplicity to an infrequent user. Product codes, version information, and a couple of dates would allow a user to hone in on the likely content topics and select content to edit from a well targeted list of search results. Relationships between content modules that are indicated in metadata can alert a user that when one object is updated, other related objects may need to be reviewed for potential update as well.

It is becoming increasingly clear that there is no one model for XML or smart content creation and editing. Just as a carpenter may have several saws, each designed for a particular type of cut, a robust smart content structured content environment may have more than one editor in use. It behooves us to design our systems and tools to meet the desired business processes and user functionality, rather than limit our processes to the features of one tool.

Repurposing Content vs. Creating Multipurpose Content

In our recently completed research on Smart Content in the Enterprise we explored how organizations are taking advantage of benefits from XML throughout the enterprise and not just in the documentation department. Our findings include several key issues that leading edge XML implementers are addressing including new delivery requirements, new ways of creating and managing content, and the use of standards to create rich, interoperable content. In our case studies we examined how some are breaking out of the documentation department silo and enabling others inside or even outside the organization to contribute and collaborate on content. Some are even using crowd sourcing and social publishing to allow consumers of the information to annotate it and participate in its development. We found that expectations for content creation and management have changed significantly and we need to think about how we organize and manage our data to support these new requirements. One key finding of the research is that organizations are taking a different approach to repurposing their content, a more proactive approach that might better be called “multipurposing”.

In the XML world we have been talking about repurposing content for decades. Repurposing content usually means content that is created for one type of use is reorganized, converted, transformed, etc. for another use. Many organizations have successfully deployed XML systems that optimize delivery in multiple formats using what is often referred to as a Single Source Publishing (SSP) process where a single source of content is created and transformed into all desired deliverable formats (e.g., HTML, PDF, etc.).

Traditional delivery of content in the form of documents, whether in HTML or PDF, can be very limiting to users who want to search across multiple documents, reorganize document content into a form that is useful to the particular task at hand, or share portions with collaborators. As the functionality on Web sites and mobile devices becomes more sophisticated, new ways of delivering content are needed to take advantage of these capabilities. Dynamic assembly of content into custom views can be optimized with delivery of content components instead of whole documents. Powerful search features can be enhanced with metadata and other forms of content enrichment.

SSP and repurposing content traditionally focuses on the content creation, authoring, management and workflow steps up to delivery. In order for organizations to keep up with the potential of delivery systems and the emerging expectations of users, it behooves us to take a broader view of requirements for content systems and the underlying data model. Developers need to expand the scope of activities they evaluate and plan for when designing the system and the underlying data model. They should consider what metadata might improve faceted searching or dynamic assembly. In doing so they can identify the multiple purposes the content is destined for throughout the ecosystem in which it is created, managed and consumed.

Multipurpose content is designed with additional functionality in mind including faceted search, distributed collaboration and annotation, localization and translation, indexing, and even provisioning and other supply chain transactions. In short, multipurposing content focuses on the bigger picture to meet a broader set of business drivers throughout the enterprise, and even beyond to the needs of the information consumers.

It is easy to get carried away with data modeling and an overly complex data model usually requires more development, maintenance, and training than would otherwise be required to meet a set of business needs. You definitely want to avoid using specific processing terminology when naming elements (e.g., specific formatting, element names that describe processing actions instead of defining the role of the content). You can still create data models that address the broader range of activities without using specific commands or actions. Knowing a chunk of text is a “definition” instead of an “error message” is useful and far more easy to reinterpret for other uses than an “h2” element name or an attribute for display=’yes’. Breaking chapters into individual topics eases custom, dynamic assembly. Adding keywords and other enrichment can improve search results and the active management of the content. In short, multipurpose data models can and should be comprehensive and remain device agnostic to meet enterprise requirements for the content.

The difference between repurposing content and multipurpose content is a matter of degree and scope, and requires generic, agnostic components and element names. But most of all, multipurposing requires understanding the requirements of all processes in the desired enterprise environment up front when designing a system to make sure the model is sufficient to deliver designed outcomes and capabilities. Otherwise repurposing content will continue to be done as an afterthought process and possibly limit the usefulness of the content for some applications.

Paper on Open Government Data Initiatives Available

Updated March 3, 2010

Government agencies produce a lot of information. Making it accessible to the public, which essentially paid for it, can be quite challenging. The volume is high. The formats are varied. Much of it remains locked in information silos.

Support is growing to take steps to make as much government information available to the public as possible. President Obama issued a directive describing the official policy for Transparency and Open Government that mandates an unprecedented level of accessibility to government information. At the same time, technical advances have improved the feasibility of increasing access to the data.

I recently completed a Gilbane paper on this topic and how some agencies are improving access to public data. It is now available for free on our Web site at https://gilbane.com/beacons.html. The paper’s sponsor, Mark Logic, has provided interesting case studies that illustrate the challenges and approaches to overcoming them. I also explore some of the major hurdles that need to be crossed to achieve this goal, including:

  1. Extremely high volumes of content and data
  2. Highly diverse, heterogeneous data formats and data models
  3. Complex content integration and delivery requirements
  4. Time-sensitivity of content
  5. Changing information environments

The approaches described have enabled that users of this technology to implement high-volume, disparate-data applications that not only overcome old technical barriers but also deliver new value to their organizations. This is, after all, the essence of open data – be it for open government, open publishing, or open enterprise.

I encourage you to read this paper to get a better understanding of what works to make government data more open.

Update: the Beacon is also available from Mark Logic.

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