VisiCalcWhat is a Killer App. (aka Killer Application)?  Wikipedia says it’s software that is so necessary, or desirable, that it drives sales of the software/hardware necessary to run it.  Investopedia defines it as “a buzzword that describes a software application that surpasses all of its competitors.”
I’ve compiled a list of the more popular killer apps. below.  The dates listed are approximate or the start of public acceptance, as opposed to the actual creation date.

Desktop PublishingThe original promise of personal computers is that they would make you more efficient and enable you to complete your work faster.  That they did, but when people saw what they were capable of they found more tasks to perform.  Then they complained that it took longer to use computers.  That’s because people were choosing to increase the content of their tasks.  This trend of increasing amounts of data and frustration over data overload has continued for a few decades.  Now it’s out of control!
SpreadsheetLooking at the list of killer apps (above) we can see that the amount of information available to us is growing faster than we can handle.  Spreadsheets encouraged the financial industry to create more financial scenarios, new ways of looking at the same old numbers and started the trend of storing data on disk.  Video Games didn’t increase our data storage much at first, because they came on cartridges.  But they did make people more comfortable with computers, which brought more young people into computers early and created a surge in new creative Video Gamesways of utilizing computers.  Desktop Publishing pulled corporate business and advertising departments into the computer revolution and introduced the need for large documents and images to be stored.
E-mail has turned out to be the worst offender in the data overload problem, and that’s not just due to SPAMInternet Service Providers (ISPs) have gradually increased the maximum E-mailattachment size to multiple megabytes.  Now, a single user can attach a multi-megabyte file to an email message and send it to a large group of people.  That message is then copied for each recipient which exponentially increases the amount of data traveling over the Internet or being stored on a single company’s intranet email server.  The size of the emails isn’t as bad as the number of emails arriving in each person’s inbox.  Sure, SPAM is a part of that problem, but once the spam is removed the remaining emails often take people 50% or more of their work day to process.  Many people experience E-mail Bankruptcy (information overload).  That’s when they can’t keep up with the emails flowing into their inbox and they give up.  These are the people who seldom respond your your emails, even when they are urgent.
The Web Browser is everyone’s favorite portal to all of the information on the Web.  It has provided even novice users with a method to reach data from any where on the planet.  Unfortunately, it is just a window into a universe of data.  It doesn’t zoom out to Web Browserprovide the bigger picture.  If you weren’t frustrated with access to too much information before the Internet, now you can feel like there is no subject to talk about where someone else, within quick access to your web content, isn’t more of an expert on your topic than you are.  Thankfully, with the Web Browser came the Search Engine.  Search Engines are great at performing text searches across the entire Internet, unfortunately you aren’t seeing the entire Internet.  At least not on the first few pages of results.  What you see is the list of web sites that do the best job at Search Engine Optimization or are willing to pay the most for advertising.  That doesn’t mean that they have the most accurate information or that their content matches your needs.  So, now you have instant access to even more information, but no way to filter the search results other than manually reading each web page.
Personal Information Managers (PIM) do a good job at managing your personal data, but they only handle a narrow list of structured data (database) types: Calendar, Contacts, E-mail, etc..  Web 2.0 applications and collaboration offer solutions for backing up your data, Instant Messengerfreeing up space on your local hard drive, and sharing live data (with others on the Web), but that also spreads your data across the Internet which can make it even harder to manage.  Finally, Web 3.0 (the Semantic Web) promises to better connect us to the information that is most pertinent to us, and enable our applications to import the data automatically.  That should improve our Search Engine experience, but it does nothing to help us manage the growing amount of information constantly being shovelled onto our computers.
With all of these wonderful “killer app” technologies fulfilling their promises of connecting us to more and more information, what do we do with it all?  Here is my approach:

  1. Locate all Data (even the data not intended to be shared/viewable)
    1. On the Internet, this means the data missed by the popular search engines.  They limit how deep they search into each web page.
    2. On your local hard drive, this means deleted or hidden files and files lost due to disorganization.
    3. In Electronic Discovery and Data Recovery, this means files maliciously hidden and intelligently carving data lost to disk corruption.
  2. Interpret the Data
    1. Identify each file type and record type (records are stored in databases).
    2. Intelligently index the data, using knowledge of each file format’s structure.
  3. Data Mine for Relevant Information
    1. Classify each file and record into categories in order to group related content together.
      1. Use the Semantic Web technology when author’s choose to cooperate with this new standard.
      2. Use categories already associated with the known file type and record type.
    2. Search for terms most pertinent to the user
      1. Use knowledge of the file structure to choose the method used, depending on the type of text data and language being searched.
      2. Use fuzzy searches to catch each mis-spelling and alternate word usage.
    3. Filter the search results by classifications and related terms.
  4. Summarize the Data for Meaningful and Applicable Conclusion(s)
    1. Specify the search request
      1. Advanced users need the ability to specify detailed searches, using Boolean logic and all of the available filters.
      2. Novice users need automatic settings that allow them to perform casual searches with a minimum number of settings used.  The solution must observe the user’s prior usage and current terms to automatically make intelligent settings that will best serve the user.
    2. Automatically create a report
      1. Use human readable text in paragraph form, using bullet points and diagrams where possible.
      2. List the search criteria used (even when the settings were made automatically).
      3. Summarize the search results, highlighting the most pertinent results and how they relate to each other.
      4. List the most relevant results, limited to a length that won’t exceed its usefulness.
      5. Conclude the results, based on the relationships between the most pertinent results.
      6. Recommend how the search settings and terms can be improved for the next run.

The results from this approach would provide what I like to call “Data Wisdom“.  That key knowledge that we currently have to spend countless hours searching and reading for.
While the technologies required for many of these steps are not yet available, we at Forensic Innovations are working on solutions to tackle each of these challenges.  File Investigator is useful in steps 1-2, 1-3, 2-1, 3-1-2, 3-2-1 & 3-3.  File Expander is used in steps 2-2 & 3-2-1.  File Harvester will support steps 1-2 & 1-3.  Our focus is providing the technologies necessary to obtain Data Wisdom using the most accurate, automated and efficient methods possible.  Where current methods are missing, or inadequate, we create our own.

Killer App: Data Wisdom

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