Category Archives: Information Architecture (IA)

People Turn Toward “Data Banks” to Commoditize on their Purchase and User Behavior Profiles

Anyone who is anti “Big Brother”, this may not be the article for you, in fact, skip it. ūüôā

 

The Pendulum Swings Away from GDPR

In the not so distant future, “Data Bank” companies consisting of¬†Subject Matter Experts¬†(SME) across all verticals, ¬†may process¬†your data¬†feeds collected from your purchase and user behavior profiles.¬† Consumers will be encouraged to submit their data profiles into a Data Bank who will offer incentives such as a reduction of¬†insurance premiums to cash back rewards.

 

Everything from activity trackers, home¬†automation, to¬†vehicular automation¬†data may be captured and aggregated. ¬† ¬†The data collected can then be sliced and diced to provide macro and¬†micro views of the information. ¬† ¬†On the abstract, macro level the¬†information¬†may allow for demographic, statistical correlations, which may¬†contribute to corporate strategy. On a¬†granular¬†view, the data¬†will provide “data banks” the opportunity to sift through data to perform analysis and correlations that lead to actionable information.

 

Is it secure?  Do you care if a hacker steals your weight loss information? May not be an issue if collected Purchase and Use Behavior Profiles aggregate into a Blockchain general ledger.  Data Curators and Aggregators work with SMEs to correlate the data into:

  • Canned, ‘intelligent’ reports targeted for a specific subject matter, or across silos of¬†data types
  • ‘Universes’ (i.e. ¬†Business Objects) of data that may be ‘mined’ by consumer approved, ‘trusted’ third party companies, e.g. your insurance companies.
  • Actionable information based on AI subject matter rules engines and consumer rule transparency may be provided.

 

¬†“Data Banks” may be required to report to their customers who agreed to sell their data examples of specific rows of the data, which was sold on a “Data Market”.

Consumers may have¬†the option of sharing their personal¬†data with specific companies by proxy, through a ‘data bank’¬†granular to the data point¬†collected.¬† Sharing of Purchase and User Behavior Profiles:

  1. may lower [or raise] your insurance premiums
  2. provide discounts on preventive health care products and services, e.g. vitamins to yoga classes
  3. Targeted, affordable,  medicine that may redirect the choice of the doctor to an alternate.  The MD would be contacted to validate the alternate.

 

The curriated data collected may be harnessed by thousands of affinity groups to offer very discrete products and services.  Purchase and User Behavior Profiles,  correlated information stretches beyond any consumer relationship experienced today.

 

At some point, health insurance companies may require you to wear a tracker to increase or slash premiums.  Auto Insurance companies may offer discounts for access to car smart data to make sure suggested maintenance guidelines for service are met.

 

You may approve your “data bank”¬†to give access¬†to specific soliciting government agencies or private firms looking to analyze data for their studies. You may qualify based on the demographic, abstracted data points collected for incentives provided may be tax credits, or paying studies.

Purchase and User Behavior Profiles:  Adoption and Affordability

If ‘Data Banks’ are allowed to collect Internet of Things (IoT)¬†device profile and the devices themselves are cost prohibitive. ¬†here are a few¬†ways to increase their adoption:

  1.  [US] tax coupons to enable the buyer, at the time of purchase, to save money.  For example, a 100 USD discount applied at the time of purchase of an Activity Tracker, with the stipulation that you may agree,  at some point, to participate in a study.
  2. Government subsidies: the cost of aggregating and archiving Purchase and Behavioral profiles through annual tax deductions.  Today, tax incentives may allow you to purchase an IoT device if the cost is an itemized medical tax deduction, such as an Activity Tracker that monitors your heart rate, if your medical condition requires it.
  3. Auto, Life, Homeowners, and Health policyholders may qualify for additional insurance deductions
  4. Affinity branded IoT devices, such as American Lung Association may sell a logo branded Activity Tracker.  People may sponsor the owner of the tracking pedometer to raise funds for the cause.

The World Bank has a repository of data, World DataBank, which seems to store a large depth of information:

World Bank Open Data: free and open access to data about development in countries around the globe.”

Here is the article that inspired me to write this article:

http://www.marketwatch.com/story/you-might-be-wearing-a-health-tracker-at-work-one-day-2015-03-11

 

Privacy and Data Protection Creates Data Markets

Initiatives such as¬†General Data Protection Regulation (GDPR) and other privacy initiatives which seek to constrict access to your data to you as the “owner”, as a byproduct, create opportunities for you to¬†sell your data.¬†¬†

 

Blockchain: Purchase, and User Behavior Profiles

As your “vault”, “Data Banks” will collect and maintain your two primary datasets:

  1. As a consumer of goods and services, a Purchase Profile is established and evolves over time.¬† Online purchases are automatically collected, curated, appended with metadata, and stored in a data vault [Blockchain].¬† “Offline” purchases at some point, may become a hybrid [on/off] line purchase, with advances in traditional monetary exchanges, and would follow the online transaction model.
  2. User Behavior (UB)¬† profiles, both on and offline will be collected and stored for analytical purposes.¬† A user behavior “session” is a use case of activity where YOU are the prime actor.¬† Each session would create a single UB transaction and are also stored in a “Data Vault”.¬† ¬†UB use cases may not lead to any purchases.

Not all Purchase and User Behavior profiles are created equal.¬† Eg. One person’s profile may show a monthly spend higher than another.¬† The consumer who purchases more may be entitled to more benefits.

These datasets wholly owned by the consumer, are safely stored, propagated, and immutable with a solution such as with a Blockchain general ledger.

Information Architecture: An Afterthought for Content Creation Solutions

Maximizing Digital Asset Reuse

Many applications that enable users to create their own content from word processing to graphics/image creation have typically relied¬†upon 3rd party Content Management Solutions (CMS) / Digital Asset Management (DAM) platforms to collect metadata describing the assets upon ingestion into their platforms.¬† Many of these platforms have been “stood up” to support projects/teams either for collaboration on an existing project, or reuse of assets for “other” projects.¬† As a person constantly creating content, where do you “park” your digital resources for archiving and reuse?¬† Your local drive, cloud storage, or not archived?

Average “Jane” / “Joe” Digital Authors

If I were asked for all the content I’ve created around a particular topic or group of topics from all my¬†collected/ingested digital assets, it may be a herculean¬†search effort spanning multiple platforms.¬† As an independent creator of content, I may have digital assets ranging from Microsoft Word¬†documents, Google Sheets spreadsheets, Twitter tweets,¬† Paint.Net (.pdn) Graphics, Blog Posts, etc.

Capturing Content from Microsoft Office Suite Products

Many of the MS Office content creation products such as Microsoft Word have minimal capacity to capture metadata, and if the ability exists, it’s subdued in the application.¬† MS Word, for example, if a user selects “Save As”, they will be able to add/insert “Authors”, and Tags.¬† In Microsoft Excel, latest version,¬† the author of the Workbook has the ability to add Properties, such as Tags, and Categories.¬† It’s not clear how this data is utilized outside the application, such as the tag data being searchable after uploaded/ingested by OneDrive?

Blog Posts: High Visibility into Categorization and Tagging

A “blogging platform”, such as WordPress, places the Category and Tagging selection fields right justified to the content being posted.¬† In this UI/UX, it forces a specific mentality to the creation, categorization, and tagging of content.¬† This blogging structure constantly reminds the author to identify the content so others may identify and consume the content.¬† Blog post content is created to be consumed by a wide audience of interested viewers based on those tags and categories selected.

Proactive Categorization and Tagging

Perpetuate¬†content classification through drill-down navigation of a derived Information Architecture Taxonomy.¬† As a “light weight” example, in WordPress, the Tags field when editing a Post, a user starts typing in a few characters, an auto-complete dropdown list appears to the user to select one or more of these previously used tags.¬† Excellent starting point for other Content Creation Apps.

Users creating Blog Posts can define a Parent/Child hierarchy of categories, and the author may select one or more of relevant categories to be associated with the Post.

Artificial Intelligence (AI) Derived Tags

It wouldn’t be a post without mentioning AI.¬† Integrated into applications that enable user content creation could be a tool, at a minimum, automatically derives an “Index” of words, or tags.¬† The way in which this “intelligent index” is derived may be based upon:

  • # of times word occurrence
  • mention of words in a particular context
  • reference of the same word(s) or phrases in other content
    • defined by the same author, and/or across the platform.

This intelligently derived index of data should be made available to any platforms that ingest content from OneDrive, SharePoint, Google Docs, etc.  These DAMs ( or Intelligent Cloud Storage) can leverage this information for any searches across the platforms.

Easy to Retrieve the Desired Content, and Repurpose It

Many Content Creation applications heavily rely on “Recent Accessed Files” within the app.¬† If the Information Architecture/Taxonomy hierarchy were presented in the “File Open” section, and a user can drill down on select Categories/Subcategories (and/or tags), it might be easier to find the most desired content.

All Eyes on Content Curation: Creation to Archive
  • Content creation products should all focus on the collection of metadata at the time of their creation.
  • Using the Blog Posting methodology, the creation of content should be alongside the metadata tagging
  • Taxonomy (categories, and tags with hierarchy) searches from within the Content Creation applications, and from the Operating System level, the “Original” Digital Asset Management solution (DAM), e.g. MS Windows, Mac

 

Information Architecture (IA): the Classification of Information (Part 2)

Karl Smith has created this timeless post on Information Architecture, which is still relevant today. The below is an excerpt of his article I found relevant to the foundation of IA.


To Each His Own

Different groups of individuals have a very specific context of use when looking for content, the descriptions they use and understand to find it and their underlying purpose in doing so. In this case, they will each require a separate structure around an entity and may require their own version of the taxonomy.

Atomic Unit of Information

Define ‚ÄėWhat is the smallest component of viable (useful) information?‚Äô and use that to model the information system. I have worked with several huge education providers and universities and the questions I ask is ‚ÄėWhat is a course?‚Äô;

  • A course has a title
  • A course has duration, with a start and an end
  • A course has a subject
  • A course has a level
  • A course has prerequisites
  • A course has an outcome, which leads to options
  • A course has a delivery mechanism

I also ask, ‚ÄėWho is a student?‚Äô, ‚ÄėWho is a tutor?‚Äô, ‚ÄėWhat is an outcome?‚Äô even ‚ÄėWhat is a college?‚Äô, if a course has a regular location then this creates a second set of entities.

  • A location has an address, telephone number, email address
  • A location has facilities
  • A location has transportation links
  • A location has a community
  • A location has accommodation

And it goes on and on, this is Information Architecture 101.

Source: Information Architecture (IA) the classification of information Part 2 ‚Äď Karl Smith