Showing posts with label Metadata. Show all posts
Showing posts with label Metadata. Show all posts

June 2, 2014

Information Where We Look

I like this short video on advances in Augmented Reality by Applied Research Associates (ARA).

ARA supports DARPA's Urban Leader Tactical Response Awareness and Visualization (ULTRA-Vis) program--to develop Augmented Reality (AR) for our soldiers. 

Augmented Reality is "Virtual icons, avatars, and messages overlaid accurately on the real world."

The purpose is to know"where you are and where objects are around you" and to "access information simply by looking at them."

The interface is a heads-up wearable display, rather than an smartphone or tablet. 

The AR integrates GPS, terrain information, commercial data, and sensors.

Further, you and others using this technology will be able to tag and share data in what I would call Social Reality (a mixture of social computing and augmented reality). 

Here your world of information is augmented by other's AR views shared with you.

AR offers an enormous opportunity to make our world far richer with information everywhere we look, rather than just when we look it up. 

For it to be ultimately successful, the display will need to be worked in as an embed or overlay on our actual eyes (like a contact lens), rather than worn like Google Glass.

For the non-soldier, not every open field needs augmented reality--in fact, it would sort of spoil the natural beauty of it--but it sure won't hurt to be able to turn it on, at will, to see which flowers are blooming and perhaps, whether there just might be a snake out there too.  ;-)

January 13, 2013

You Can Better The World

I am really excited about this new Social Media application called Betterific.

It looks a lot like Twitter but is focused on ideas to better the world. 

Every Betterific starts under the heading of "Wouldn't it be better if" and you fill in the rest. 

Whether you have ideas for improving products, companies, policies, or even the way we treat each other--this is a great way to get your ideas out there. 

You also add tags (metadata) to make the ideas more easily searchable by others. 

Like Twitter you can follow topics or other innovative people, friends, and family members. 

A great feature is that you can actually vote--thumbs up or down--for the ideas, and through crowdsourcing great ideas can rise to the top.

There is also a bar at the top where you can look up better ideas by search term--so individuals, organizations, or brands can harvest this information and hopefully act on them.

One of the featured Betterifics when you sign in online is from someone who suggested that toilet seats come with a pedal lift lid (like a garbage can)--being a little germophobic myself, I vote definitely yes to this one!

I hope this type of app catches on so we can all innovate and get our ideas out there simply and clearly.

This has the potential to become a tremendous archive for great ideas that can be accessed, prioritized and most importantly implemented--so we can all really make a difference for the better. ;-)

(Source Photo: Andy Blumenthal)


June 5, 2011

Video Surveillance Made Easier

One of the big problems with video surveillance is that even the most alert security team can be lulled by fatigue and boredom into missing critical events and details on the closed-circuit television (CCTV).

Now there is a new technology called BriefCam (founded in 2007) from Hebrew University in Israel that summarizes hours of video in brief minutes.

What differentiates this new technology, according to The Economist (15 February 2011) is that rather than fast-forwarding or using motion detection to capture or select images, BriefCam captures everything, but "creates a summary of all moving events and play back a synopsis...not speeded up, each person moves at their actual pace. And at any time during the review an operator can switch [click-on the time stamp of the event of interest] to see the original video footage."

BriefCam creates like a time warp where "all moving events from the period of interest are collected and shifted in time to create the synopsis."

Essentially objects are overlaid on a timeless background, so you are seeing them occur simultaneously, each with a timestamp that can be selected and clicked to isolate the event.

What makes this an incredible forensic tool, is that there are controls for speed and density of what you watching, and for even moving objects out of the way on the screen.

The Chairman of BriefCam explains, "We don't try to replace human eyes, we just report what we see so that it is more comprehensible."

This is particularly helpful since according to CNBC (July 2010), which awarded BriefCam as number 2 of Europe's 25 Most Creative Companies, noted "the average person viewing surveillance footage has an effective attention span of about [only] 20 minutes."

This is why BriefCam can help our law enforcement and security personnel overcome the traditional video surveillance issues that the Wall Street Journal (27 September 2010) put as "there's not enough time and manpower to watch it all." This is one reason that the WSJ awarded BriefCam their 2010 Innovation Award.

Potential customers for this physical security technology includes police, homeland security, military, as well as commercial customers.

This is a very promising technology tool that with the addition or integration of recognition software and metadata tagging can help us monitor and safeguard our borders, streets, and critical infrastructure.


January 27, 2011

Safeguard Your Location

Nice presentation by the Army called "Geotags and Location-based Social Networking."

It offers important information on the potential dangers of leaving on Global Positioning System (GPS) services on electronic devices (such as smartphones and cameras) and using location-based social networking services.

- "Geotagging is the process of adding geographical identification to photographs, videos, websites, and SMS messages. It is the equivalent of adding a 10-digit coordinate to everything you post on the Internet."
- Location-based social networking applications focus on 'checking-in' at various locations to earn points, badges, discounts" and even become mayor for the day.

Exposing your location is not only dangerous if your in the military and engaged on an operation. But rather, for all of us, broadcasting location and patterns of movement can be detrimental to personal privacy and security.

As the geotagging safety presentation advises, consider when (and when not) to:

  1. Turn off the GPS on devices such as smartphones and cameras.
  2. Keep geocoded photos offline from the Internet (i.e. Flikr, Picasa, etc.)
  3. Avoid use of location-based social networking services (e.g. FourSquare, Facebook Places, Gowalla, SCVNGR, etc.)

Sharing information--including where you are, were and are going--with family, friends, and colleagues can be a healthy and fun interchange; but sharing that information with "the wrong" people can leave you exposed and sorry.

Think twice--think about your privacy and security.


June 7, 2009

Digital Object Architecture and Internet 2.0

There is an interesting interview in Government Executive, 18 May 2009, with Robert Kahn, one of the founders of the Internet.

In this interview Mr. Kahn introduces a vision for an Internet 2.0 (my term) based on Digital Object Architecture (DOA) where the architecture focus is not on the efficiency of moving information around on the network (or information packet transport i.e. TCP/IP), but rather on the broader notion of information management and on the architecture of the information itself.

The article states: Mr Kahn “still harbors a vision for how the Internet could be used to manage information, not just move packets of information” from place to place.

In DOA, “the key element of the architecture is the ‘digital element’ or structured information that incorporates a unique identifier and which can be parsed by any machine that knows how digital objects are structured. So I can take a digital object and store it on this machine, move it somewhere else, or preserve it for a long time.”

I liked the comparison to electronic files:

“A digital object doesn’t become a digital object any more than a file becomes a file if it doesn’t have the equivalent of a name and an ability to access it.”

Here are some of the key elements of DOA:

  • Handles—these are like file names; they are the digital object identifiers that are unique to each and enable each to be distinctly stored, found, transported, accessed and so forth. The handle record specifies things like where the object is stored, authentication information, terms and conditions for use, and/or “some sense of what you might do with the object.”
  • Resolution system —this is the ‘handle system’ that “gives your computer the handle record for that identifier almost immediately.”
  • Repository—“where digital objects may be deposited and from which they may be accessed later on.” Unlike traditional database systems, you don't need to know a lot of the details about it to get in or find what you're looking for.
  • Security at object layer—In DOA, the security “protection occurs at the object level rather than protecting the identifier or by providing only a password at the boundary.”

The overall distinguishing factor of DOA from the current Internet is that in the current Internet environment, you “have to know exactly where to look for certain information” and that’s why search engines are so critical to indexing the information out there and being able to find it. In contrast, in DOA, information is tagged when it is stored in the repository and given all the information up front about “how do you want to characterize it” and who can manage it, transport it, access it, and so on.

To me, in DOA (or Internet 2.0) the information itself provides for the intelligent use of it as opposed to in the regular Internet, the infrastructure (transport) and search features must provide for its usability.

As I am thinking about this, an analogy comes to mind. Some people with medical conditions wear special information bracelets that identify their unique medical conditions and this aids in the speed and possibly the accuracy of the medical treatment they receive—i.e. better medical management.  This is like the tagging of information in DOA where the information itself wears a metaphorical bracelet identifying it and what to do with it thereby yielding faster and better information management.

Currently, we sort of retrofit data about our information into tags called metadata, but instead here we have the notion of creating the information itself with the metadata almost as part of the genetic makeup of the information itself.

Information with “handles” built into as a part of the information creation and capture process would be superior information for sharing, collaboration, and ultimately more user-centric for people. 

In my humble opinion, DOA has some teeth and is certainly not "Dead On Arrival."


November 13, 2008

The Awesome Implications of Gmail and Enterprise Architecture

Recently, I took the leap from Yahoo! and added a Gmail Account.

For a long time, I thought, “What can be the difference? E-mail is e-mail.” Further, I thought people were just switching because it was the latest fad, and they wanted to be associated with the then-upcoming Google versus the troubled Yahoo!

While this may be partly true, there are some tangible advantages to Gmail. Gmail has a better interface than Yahoo!—it provides one look and feel while Yahoo! has a switching mechanism between the legacy email and a new Yahoo! mail, which is still kind of quirky. Gmail better integrates other tools like instant messaging and VOIP. Gmail offers a huge amount of storage. Gmail associates email strings so you can easily expand or click through the chain.

And finally,
Gmail has a label structure for emails versus Yahoo’s folder structure. This is the one that matters most.

The label structure is superior to the folders. You can have multiple labels for an e-mail and can therefore locate items of interest much more easily by checking in any of the pertinent label categories. In contrast, in the Yahoo! folder structure, you can only store the e-mail in one folder, period. This makes it it difficult to store, connect, and discover items that cross categories.

For example, if you have e-mails on enterprise architecture topics from a particular source, you may want to label it by the topic EA and by the source it came from, so in the future you can find it by topic or by source.

Reflecting on this archiving structure from an enterprise architecture perspective, it became apparent to me that the legacy folder structure used in Yahoo! mail and the typical Microsoft Office applications such as Outlook and My Documents is built according to a typical taxonomy structure. By this I mean that here are one “parent” to multiple “children” relationships (i.e. a folder has one or more files/emails, but a file/email is constrained to only one folder).

However, in Gmail, the archiving structure is built according to an ontology structure, where there are multiple relationships between objects, so that there is a many-to-many relationship. (i.e. a label category can have multiple files/emails and files/emails can be tagged to many labels)—a much more efficient and expansive metadata structure.

So in short, the analogy goes like this--

Folder structure : Taxonomy : : Labels : Ontology

And Google wins in e-mail archiving hands down!

In enterprise architecture, the implications are enormous. For example, Microsoft, which is the defacto standard in most of our organizations, rules the way we store files in the legacy folder structure. Perhaps, the time has come for us to evolve to the superior metadata structure using labeling. This will make it far easier and more productive for the average user to search and discover information they need.

Further, metadata is at the heart of enterprise architecture, where we seek to break down the siloes in and between our organizations and make for better interoperability and information sharing. The goal is a holistic view of what’s going on in our organization and between organizations, and the only way to achieve that from an IT perspective is to label information so that it is discoverable and usable outside stereotypical stovepipes.


April 25, 2008

Enterprise Information Architecture

We all know that enterprise architecture is a strategic-level synthesis of business and technology information to drive enhanced decision-making. To develop the EA we must build out the individual perspectives, such as performance, business, information, services, technology, security, and human capital. This blog focuses on one of those, enterprise information architecture.

Enterprise Information Architecture (EIA) is the strategic-level information architecture for the organization.

Note: Information refers to both information (processed data) and data.


The overall goal of EIA is to provide the right information to the right people anytime, anywhere.



The federal mandate in law enforcement is the Intelligence Reform and Prevention Act (IRTPA) of 2004. Further, The Office of the Director of National Intelligence (ODNI) has developed the Information Sharing Environment (ISE) Implementation Plan in 2006 and the Department of Defense created the Net-centric Data Strategy in 2001.

Common Sense:

We need information to perform our mission/business function and processes: we can’t do without it! Moreover, in an information economy, information is power and information is currency.


Developing the enterprise information architecture is an outgrowth of developing the business, data, and system models to understand the business processes, the information required to perform those, and the systems that serve up the information.

According to the Federal Enterprise Architecture, Data Reference Model, there are three parts to developing your information architecture.

  1. Data Descriptions—identify what your information needs are.
  2. Data Context—determining how the information is related.
  3. Data Sharing—developing the mechanisms for discovering and exchanging information.

Data Descriptions is the semantics and syntax. It involves developing your “data asset catalogue” and the metadata. This includes developing a lexicon or data dictionary with harmonized terms and schemas to describe them, as well as tagging the data. This helps define what the terms mean and identifies the rules for arranging them.

Data Context is the relationships. It includes categorizing the information using taxonomies and ontologies. It includes developing models, such as entity relationship diagrams (ERDs) to identify entities or information objects (and their attributes or properties) and associating them.

Data Sharing is the transactional processes. It entails the decomposition of information exchanges (in an Information Exchange Matrix or in a Information Exchange Package Description, IEPD) to determine the provider, the consumer, the trigger, the frequency, the media, the security, and so forth for each type of transaction. This phases also includes developing information repositories/registries, information sharing access agreements, and other mechanisms for sharing the information, such as portals, web services, enterprise service bus (ESB), and so on.

In the end, EIA is about transforming the organization: Culturally, from information hoarding to information sharing; from a business process perspective, optimizing information flows and usage, and in terms of governance, managing information as an enterprise asset.


February 4, 2008

Web 3.0 and Enterprise Architecture

While the Web 1.0 is viewed as an information source, and Web 2.0 as participatory, Web 3.0 is envisioned as Semantic (or the Semantic Web).

MIT Technology Review, March 2007 reports in an article entitled “A Smarter Web” by John Borland that Web 3.0 will “give computers the ability—the seeming intelligence—to understand content on the World Wide Web.” The goals is to “take the web and make it …a system that can answer questions, not just get a pile of documents that might hold an answer.”

In The New York Times, November 2007, John Markoff defined Web 3.0 “as a set of technologies that offer efficient new ways to help computers organize and draw conclusions from online data.”

Not only individuals would benefit from the Semantic Web, but companies too that “are awash in inaccessible data on intranets, in unconnected databases, even on employees’ hard drives.” The idea is to bring the data together and make it useful.

Many of you have heard of the Dewey Decimal System for organizing information. Melvin “Dewey was no technologist, but the libraries of his time were as poorly organized as today’s Web. Books were often placed in simple alphabetical order, or even lined up by size…Dewey found this system appalling: order, he believed, made for smoother access to information.” (MIT Technology Review) Melvin Dewey developed in 1876 what became The Dewey Decimal System, a library classification attempts to organize all knowledge.” (Wikipedia) In the Dewey system, books on a similar subject matter are co-located aiding discovery and access to information.

MIT Technology Review contends that like Melvin Dewey, web browser and search engine companies, like Microsoft and Google, want to help consumers locate information more efficiently.

“By the mid-1990’s, the computing community as a whole was falling in love with the idea of metadata, a way of providing Web pages with computer-readable instruction or labels…metadata promised to add the missing signage. XML—the code underlying today’s complicated websites, which describes how to find and display content, emerged as one powerful variety.” The problem with this was that it was not a systematic way of labeling data, since each developer used “their own custom ‘tags’—as if different cities posted signs in related but mutually incomprehensible dialects.”

In 1999, the World Wide Web Consortium (W3C) came up with the Resource Description Framework (RDF) for locating and describing information. Since then the vision has been for “a web that computers could browse and understand much as humans do…analogous to creating detailed road signs that cars themselves could understand and upon which they could act,” independent of human action. However, the obstacles remain for how to create ontologies that everyday busy people would use to relate data across the web—data that is currently described in myriad number of ways today—so that computers could then read and understand the data.

A second area of doubt on the realism of a Semantic Web is whether computers can truly understand the intricacies (or connotations) of human language. For example, can a computer realistically make sense of a word like marriage that can have subtle distinctions of “monogamy, polygamy, same-sex relationships, and civil unions?”

Despite the perceived obstacles, many remain not only fixated, but enamored with the notion of a Semantic Web that can not only provide amazing amounts of information, but also, like a human being, is able to analyze the data holistically, and provide actionable artificial intelligence (AI).

To enterprise architects, the Semantic Web (or Web 3.0) would be an incredible leap forward enabling organizations and individuals to get more intelligence from the web, be more productive, and ultimately provide for more efficient and effective business processes, supported by a higher order of computing enablement. Additionally, for enterprise architects themselves that deal with inordinate amounts of business and technical data—structured and unstructured—Web 3.0 technologies and methods for better mining and analyzing the data would be a welcome capability for advancing the discipline.


November 5, 2007

Semantic Web and Enterprise Architecture

MIT Technology Review, 29 October 2007 in an article entitled, “The Semantic Web Goes Mainstream,” reports that a new free web-based tool called Twine (by Radar Networks) will change the way people organize information.

Semantic Web—“a concept, long discussed in research circles, that can be described as a sort of smart network of information in which data is tagged, sorted, and searchable.”

Clay Shirky, professor in the Interactive Telecommunications Program at New York University says. “At its most basic, the Semantic Web is a campaign to tag information with extra metadata that makes it easier to search. At the upper limit, he says, it is about waiting for machines to become devastatingly intelligent.”

Twine—“Twine is a website where people can dump information that's important to them, from strings of e-mails to YouTube videos. Or, if a user prefers, Twine can automatically collect all the web pages she visited, e-mails she sent and received, and so on. Once Twine has some information, it starts to analyze it and automatically sort it into categories that include the people involved, concepts discussed, and places, organizations, and companies. This way, when a user is searching for something, she can have quick access to related information about it. Twine also uses elements of social networking so that a user has access to information collected by others in her network. All this creates a sort of ‘collective intelligence,’ says Nova Spivack, CEO and founder of Radar Networks.”

“Twine is also using extremely advanced machine learning and natural-language processing algorithms that give it capabilities beyond anything that relies on manual tagging. The tool uses a combination of natural-language algorithms to automatically extract key concepts from collections of text, essentially automatically tagging them.”

A recent article in the Economist described the Semantic Web as follows:

“The semantic web is so called because it aspires to make the web readable by machines as well as humans, by adding special tags, technically known as metadata, to its pages. Whereas the web today provides links between documents which humans read and extract meaning from, the semantic web aims to provide computers with the means to extract useful information from data accessible on the internet, be it on web pages, in calendars or inside spreadsheets.”

So whereas a tool like Google sifts through web pages based on search criteria and serves it up to humans to recognize what they are looking for, the Semantic Web actually connects related information and adds metadata that a computer can understand.
It’s like relational databases on steroids! And, with the intelligence built in to make meaning from the related information.

Like a human brain, the Semantic Web connects people, places, and events seamlessly into a unified and actionable ganglion of intelligence.

For User-centric EA, the Semantic Web could be a critical evolution in how enterprise architects analyze architecture information and come up with findings and recommendations for senior management. Using the Semantic Web, business and technology information (such as performance results, business function and activities, information requirements, applications systems, technologies, security, and human capital) would all be related, made machine readable, and automatically provide intelligence to decision-makers in terms of gaps, redundancies, inefficiencies, and opportunities—pinpointed without human intervention. Now that’s business intelligence for the CIO and other leaders, when and where they need it.


September 3, 2007

Business Intelligence and Enterprise Architecture

“Business intelligence (BI) refers to applications and technologies that are used to gather, provide access to, and analyze data and information about company operations. Business intelligence systems can help companies have a more comprehensive knowledge of the factors affecting their business, such as metrics on sales, production, internal operations, and they can help companies to make better business decisions.” (Wikipedia)

Business intelligence includes warehousing data and mining data (sorting large amounts of data to find relevant information). Metadata (data about data) aids in the mining of useful nuggets of information. The warehousing and mining of data for business intelligence is often referred to as a decision support system.

User-centric EA is business (and technology) intelligence!

  • EA is a knowledge base and warehouse of information: BI warehouses date for decision support applications in the organization. Similarly, EA synthesizes and stores business and technical information across the enterprise to enable better decision making. EA uses applications like Systems Architect, DOORS, Metis, Rationale, and others to capture information in a relational database repository and model business, data, and systems. The intent is to develop a knowledge base for the capture, mining and analysis of data to enhance IT planning and governance.
  • EA provides for mining, querying, and reporting: BI tools use online analytical processing (OLAP) tools like Cognos, BusinessObjects, Hyperion, and SAS that utilize multi-dimensional database cubes for manipulating data into different views, and provides for analysis and reporting. Similarly, User-centric EA provides for analysis and reporting of performance measures, business functions, information requirements, applications systems, technology products and standards, and security measures. While EA tools are more limited than general BI tools in terms of OLAP capabilities like online queries, I believe that these tools will move in this direction in the future.
  • EA uses information visualization to communicate effectively: BI tools provide executive dashboard capabilities for displaying executive information in a user-friendly GUI format. Like an executive dashboard, EA often displays business and technology information in profiles and models that make extensive use of information visualization to communicate effectively and at strategic, high-level views to decision makers.

In is the role of the chief enterprise architect to sponsor, communicate, and educate on the use of EA for business and technology intelligence in the organization.


August 28, 2007

Data Architecture Done Right

Data architecture done right provides for the discovery and exchange of data assets between producers and consumers of data.

Data discovery is enabled by data that is understandable, trusted, and visible.

Data exchange is facilitated by data that is accessible and interoperable.

Together, data discovery and exchange are the necessary ingredients for information sharing.

Why is it so hard?

Primarily it’s a coordination issue. We need to coordinate not only internally in our own organization (often already large and complex), but also externally, between organizations — horizontally and vertically. It’s quite a challenge to get everyone describing data (metadata) and cataloging data in the same way. Each of us, each office, each division, and so forth has its own standards and way of communicating. What is the saying, “you say poTAYtos, and I say poTAHtos”.

Can we ever get everyone talking the same language? And even if we could, do we really want to limit the diversity and creativity by which we express ourselves? One way to state a social security number is helpful for interoperability, but is there really only one "right" way to say it? How do we create data interoperability without creating only one right way and many wrong ways to express ourselves?

Perhaps, the future will bring artificial intelligence closer to being able to interpret many different ways of communicating and making them interoperable. Sort of like the universal translator on Star Trek.