The Question for Content in Context: Standards and Semantics for Interoperability

THE QUEST FOR CONTENT IN CONTEXT Using standards and semantics for interoperability © Rahel Anne Bailie, Founding CEO and Principal Consultant at Content, Seriously

OVERVIEW OF PRESENTATION We will cover: ▪ The difference between data and content. ▪ Content and context. ▪ Content interoperability. ▪ Making more effective content, more effectively. ▪ Combining strengths of content and data.

CONTENT VS DATA Similarities and differences

DIFFERENCES BETWEEN CONTENT AND DATA Narrative Visualisation Building blocks

UNDERSTANDING CONTENT Models of text comprehension describe and explain the processes involved in understanding and remembering verbal information. (International Encyclopedia of the Social & Behavioral Sciences, 2001) The band graph depicts Napoleon’s army departing the PolishRussian border. A thick band shows the size of his army at specific geographic points during their advance and retreat. The diagram displays 6 types of data in 2 dimensions: the number of Napoleon’s troops, the distance travelled, the temperature, latitude and longitude, direction of travel, and location relative to specific dates.

UNDERSTANDING DATA Over 50% of study subjects had trouble interpreting statistical data, particularly when presented as probabilities instead of natural frequencies. (Science Daily, 2018) Data is a visual medium – data visualisations. (Charles Joseph Minard, via Edward Tufte)

BUILDING BLOCKS TO KNOWLEDGE Knowledge Information

• Context + Context Content + Context Data

CONTENT AND CONTEXT If content is king, then context must be the empress

CONTENT AND CONTEXT Context Normalising and rationalising Creating, enriching, context-building

CONTEXT IS EVERYTHING What is the meaning of 42? 1. The ASCII symbol for *. 2. A data point. 3. A whole number between 41 and 43. 4. The answer to the ultimate question of life, the universe, and everything. 5. The total of my last grocery bill. 6. A week in October.

DATA MANIPULATION Normalisation – structure a database to reduce redundancy and improve data integrity. Standardisation – convert data to a common format to enable processing and analysis. Rationalisation - creates/extends an ontology for a domain into the structured data world.

CONTENT MANIPULATION Development – create content with relevance, accuracy, informativeness, timeliness, engagement, and editorial standards in mind. Editing – structure a body of content to reduce redundancy and improve content integrity, including standardisation – rewrite content to fit common conventions to enable processing and analysis. Reviews and approvals – submit to workflow, capture audit trail data, enforce editorial guidelines, and check quality control against standards. Enrich - creates/extends an ontology for a domain into the structured content world.

CONTENT INTEROPERABILITY Schema and standards

INTEROPERABILITY Conventions Standards Semantics

CONVENTIONS ARE NOT STANDARDS A convention is a usual way of presenting information. Aids in comprehension. Lots of discretion in expression, in placement, in attributes.

STANDARDS Standards are technical schemas. There are two leading general schemas at the moment: ▪ Presentation side – Schema – microformats that help with search and intent. ▪ Back end – DITA XML – topicbased modules that helps authors work more efficiently.

SEMANTICS: IT’S ALL ABOUT THE METADATA Three types of metadata: ▪ Administrative ▪ Structural (Elements) ▪ Descriptive (Attributes) Reduce maintenance overhead of multiple instances with smart use of metadata. <returns>Finding the right right size size online online can be <GB>Finding the tricky, sobewe promise that you can return any can<CA>Finding tricky, so we promise that the right size online items that don’t fit. youcan canbereturn any items that don’t tricky, so we promise that <AU>Finding the right size online fit. <GB>We will pay for postage and youcan can that don’t bereturn tricky,any so items we promise that packaging via Royal Mail.</GB> Wefit.will postage and that don’t youpay canfor return any items packaging Mail. and handling <CA>We will via payRoyal for shipping fit. We willPost.</CA> pay for shipping and via Please Canada ensure you put enough handling via Canada Post. and We will pay for shipping postagewill on pay the box.</GB> <AU>We for postage and handling handling viayou Australia Post. via Australia Post.</AU> Please ensure put enough onensure the Pleaseyou you putpostage enough on the Pleasepostage ensure putbox.</CA> enough postage on the box.</AU> box.</returns>

EFFECTIVE AND EFFICIENT Content operations

SMARTER, NOT HARDER Authoring Processing Delivery

AUTHORING Production-grade authoring environment: Monitored single source of truth (Create Once, Delivery Anywhere). Efficient creation and configuration of content through use of metadata. Working environment Ontology Repository Quality

PROCESSING Automate the processing of content: Source content is burst and recombined in into multiple outputs. Used for personalisation, omnichannel needs, and other segmentation. Working environment Ontology Repository Quality Processing environment

DELIVERY Offered, not published: Publication-ready content objects sit within a delivery server. Pulled by downstream presentation systems as needed. Working environment Ontology Repository Quality Processing environment Delivery environment

PLAYING TO THEIR STRENGTHS Smart data and intelligent content

Smart data Intelligent content Joint operations

SMART DATA Smart data refers to smaller sets (compared to big data) of valuable and actionable information, and focuses on creating value, meaning, and accuracy (veracity) for some sort of purpose or outcome. Smart data is more actionable (than big data) and helps a business function gain critical insights or make important decisions. (study.com)

INTELLIGENT CONTENT Intelligent content is: ▪ Structurally rich – uses structure with semantics. ▪ Semantically aware – tagged with metadata to indicate intent. which makes the content objects: ▪ Discoverable – by search engines, internal search, or in aggregation. ▪ Re-usable – is created once, then delivered anywhere it’s needed. ▪ Reconfigurable – format-free, to be configured for any output. ▪ Adaptable – able to be adapted to multiple contexts.

OPERATIONALISING CONTENT + DATA We can do more with intelligent content + smart data Organisations already focus on data integrity and semantics It’s time to spend some time focusing on operationalising content, too Content Info Data Knowledge

QUESTIONS? Rahel Anne Bailie; Content, Seriously Designing robust content ecosystems London, UK ContentSeriously.co.uk