Context Brings Data to Life

Discover how the application of contextual computing applies real meaning to data

Virtual oceans of data are being created, and yet only a small fraction of that data is effectively leveraged by organizations. As a result, the vast majority of data today is nothing more than an asset lying dormant and hindering the search for useful information needed for a specific purpose. Given that mankind has been formally exploring the oceans for more than 200 years yet 95 percent of this realm still remains unknown,1 is the possibility of fully exploring and analyzing the oceans of data we continue to create even realistic? Probably not, considering the exponential growth rate of data.

To be successful in this big data world, organizations need to be smart in how they approach data to unlock its full value and make sense of their complex environments. And in that regard, context is vital.

A character on an American television program once remarked, “I’m not convinced I know how to read; I’ve just memorized a lot of words.”2 The line was said in jest, but it is relevant to the subject of context. What differentiates the ability to read from simply memorizing large volumes of words? Context.

Context is defined as “the parts of a discourse that surround a word or passage and can throw light on its meaning,” and “the interrelated conditions in which something exists or occurs.”3 Context allows people to draw meaning from a word based on certain conditions surrounding its use. Reading entails interpreting the context of words in real time based on how they are used in phrases or sentences.

Humans derive context from relationships, rules, and other conditions learned and experienced over time. How can systems or solutions be enabled to perform a similar function with volumes of large and/or seemingly complex data? Contextual computing aims to address this challenge.

The value of context

Without context, the potential value of an enterprise’s data is not being fully realized. Context is, in effect, a multiplier of value for data. Context is what gives meaning to data. Data without context is meaningless, and meaningless data has no value.

The more context people can provide around data elements, the more valuable the individual pieces become and the greater potential there is for the importance of an organization’s aggregate data. Moreover, every time context is added to a data element, there is a dramatic, corresponding change to the understanding of the meaning of the data. Relationships between people, places, and organizations provide the context for deep situational understanding, which helps drive enhanced, well-informed decisions and effective actions. When an end user evaluates a single record to support a potential action or decision, and there are other related data elements that exist but are not available, the resulting absence of context creates the potential for poor decision making. In addition, the likely value of an enterprise’s data is not being fully realized.

Contextual computing accelerates the detection of complex patterns in both data and processes through four key activities:

  • Gathering: Collect relevant data from multiple sources—volume and variety—and keep it as long as possible.
  • Connecting: Extract features and create metadata from diverse data sources—both structured and unstructured—to continually build and update context.
  • Reasoning: Analyze data in context to uncover hidden information and find new relationships.
  • Adapting: Compose recommendations and use context to deliver insights to the point of action, whether the client is a system or a human decision maker.

In all four of these activities, context computing systems continually learn from end-user behavior and interaction patterns to enhance the context over time. Where can context add value in an organization? The following business scenarios describe instances in which context and the application of contextual computing can be extremely valuable:

  • Making guesses or hypotheses that are required to move forward with decisions on a course of action. Context helps direct which hypotheses to make.
  • Possessing the ability to link pieces of data together that impact the quality of decision making. Context can be the linking information.
  • Having a discovery element in situations where there may be uncertainty around which data elements may be relevant to context.
  • Performing data cleansing that is typically required to derive value from data noise. Noisy data is meaningless by itself and cannot be understood and interpreted correctly by machines—for example, unstructured text.
  • Needing to leverage data from multiple sources for a specific decision in situations where master data files don’t exist or are unreasonable to create and maintain. For example, a health organization may want to obtain relevant patient information for diagnosis and treatment where it is unreasonable or unrealistic to store all the data in a single data record.

The potential for context

Context for data is the future. How will your organization respond? To learn more about context and context computing, a new study, “Empowering Governments Through Contextual Computing,” is available from the IBM Institute for Business Value (IBV).4 It identifies the opportunities and implications for contextual computing, and offers key recommendations for bringing context to organizations. Check it out.

Please share any thoughts or questions in the comments.

1 National Ocean Service, National Oceanic and Atmospheric Administration website.
2 New Girl, Season 3, Episode 3: “Double Date Quotes,” TV Fanatic website.
3 Merriam-Webster’s Collegiate Dictionary, Eleventh Edition, Merriam-Webster, Inc., 2003.
4Empowering Governments Through Contextual Computing,” IBM Institute for Business Value website.