Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

April 8, 2014

Blog Odometer Reads: 10,000 (with this post)

Filed under: Marketing,Topic Maps — Patrick Durusau @ 6:11 pm

I haven’t been posting as heavily every day for the last week or so. Mostly because I wanted to have something special for post #10,000. That “something special” is still a couple of weeks away but I do have observations to mark post #10,000 on this blog.

First and foremost, I have been deeply impressed with the variety of projects seeking to make information easier to retrieve, use and archive. Those are just on the ones I managed to find and post about. I have literally missed thousands of others. My apologies for missing any of your favorite projects and consider this an open invitation to sent them to my attention: patrick@durusau.net.

Second, I have been equally saddened by the continued use of names as semantic primitives, that is without any basis for comparison to other names. A name for an element or attribute may be “transparent” to some observers today, but what about ten (10) years from now? Or one hundred (100) years from now? Many of our “classic” texts survive in only one copy or even multiple fragments. Do you really want to rely on chance documenting of data?

Thousands if not hundreds of thousands of people saw the pyramids being built. Such common knowledge they never bothered to write down how it was done. Are you trusting mission critical applications with the same level of documentation?

Third, the difference between semantic projects that flourish and less successful projects isn’t technology, syntax, or an array of vendors leading the band. Rather, the difference is one of ROI (return on investment). If your solution requires decades of investment by third parties who may or may not choose to participate, however clever your solution, it is DOA.

Despite my deep interest in complex and auditable identity based information systems, those aren’t going to be market leaders. Weapons manufacturers, research labs, biomedical, governments and/or wannabe governments are their natural markets.

The road to less complex and perhaps in some ways unauditable identity based information systems has to start with what subjects are you not going to identify? It’s a perfectly legitimate choice to make and one I would be asking about in the world of big data.

You need to know which subjects are not documented and which subjects are documented. As a conscious decision. Unless you don’t mind paying IT to reconstruct what might have been meant by a former member of IT staff.

Fourth, the world of subjects and the “semantic impedance” that Steve Newcomb identified so long ago, is increasing at an exponential rate.

Common terminologies or vocabularies emerge in some fields but even there the question of access to legacy data remains. Not to mention that “legacy” is a term that moves a frame behind our current stage of progress.

Windows XP, used by 95% of bank ATMs becomes unsupported as of today. In twelve short years XP has gone from being “new” software, to being the standard software, now legacy software and in not too many years, dead software.

What are your estimates for the amount of data that will die with Windows XP? For maximum impact, give your estimate in terms of equivalents to the Library at Alexandria. (An unknown amount but it has as much validity as many government and RIAA estimates.)

Finally, as big data and data processing power grows, the need and opportunity for using data from diverse sources grows. Is that going to be your opportunity or the opportunity someone else has to sell you their view of semantics?

I am far more interested in learning and documenting the semantics of you and your staff than creating alien semantics to foist on a workforce (FBI Virtual Case Management project) or trying to boil some tide pool of the semantic ocean (RDF).

You can document your semantics where there is a business, scientific, or research ROI, or you can document someone else’s semantics about your data.

Your call.

If you have found the material in this blog helpful (I hope so), please consider making a donation or send me a book via Amazon or your favorite bookseller.

I have resisted carrying any advertising because I find it distracting at best and at worse it degrades the information content of the blog. Others have made different choices and that’s fine, for their blogs.

March 31, 2014

The High Cost of Lying

Filed under: Cybersecurity,Marketing,Security — Patrick Durusau @ 8:24 pm

The Surprisingly Large Cost of Telling Small Lies by Rebekah Campbell.

From the post:

Recently, I caught up with one of our angel investors for lunch: Peter is a brilliant entrepreneur from England who has lived all over the world. He has built several businesses and now lives a dream life with a house on a harbor, a happy family and a broad smile.

As our conversation drifted from an update of my company to a deep discussion about life itself, I asked him what he thought was the secret to success. I expected the standard “never give up” or some other T-shirt slogan, but what he said took me by surprise. “The secret to success in business and in life is to never, ever, ever tell a lie,” he said.

That stumped me. I know that lying is bad and telling the truth is good — we learn that as children. But the secret to success? I looked at Peter, confused and skeptical. He nodded and assured me, “Complete honesty is the access to ultimate power.”

As we spoke, I started thinking about the little lies I tell every day — often without thinking about it, but not always. I have been guilty of exaggerating a metric here or there or omitting facts for my own advantage. Each time, there is a little voice inside my head that tells me it is the wrong thing to do. I have wondered whether everyone does this or whether it is just me. Could this be what has been holding me back?

I did some research and it seems most of us lie quite a bit. A study by the University of Massachusetts found that 60 percent of adults could not have a 10-minute conversation without lying at least once. The same study found that 40 percent of people lie on their résumés and a whopping 90 percent of those looking for a date online lie on their profiles. Teenage girls lie more than any other group, which is attributed to peer pressure and expectation. The study did not investigate the number of lies told by entrepreneurs looking for investment capital, but I fear we would top the chart.

We all need to read Rebekah’s post at least once a month, if no more often.

What really annoys me are techno lies. Where you ask about one issue and the response is a lot of bluff and bluster about how the questioner doesn’t understand the technology, community, some unspecified requirements, etc.

When I get that response, I know I am being lied to. If the person had a real answer, they would not have a stock paragraph that keeps repeating the careful consideration some group made of the question at some unspecified time.

They would just say: sorry, here are the facts (a short list) and this is why X works this way. Quite simple.

BTW, there is a side-effect (sorry functional programming fans) to not lying: You don’t have to remember what lie you told to who in what context. Greatly reduces the amount of clutter than you have to remember.

At least if you want to be a successful liar. I would rather be successful at something else.

PS: Would you consider closed source software that was compromised to spy on you as lying? As in lying to a customer? I would too.

March 20, 2014

Topic Map Marketing Song?

Filed under: Marketing,Topic Maps — Patrick Durusau @ 8:29 am

Analysis of 50 years of hit songs yields tips for advertisers

Summary:

Researchers have analyzed 50 years’ worth of hit songs to identify key themes that marketing professionals can use to craft advertisements that will resonate with audiences. The researchers used computer programs to run textual analysis of the lyrics for all of the selected songs and analyzed the results to identify key themes. The researchers identified 12 key themes, and related terms, that came up most often in the hit songs. These themes are loss, desire, aspiration, breakup, pain, inspiration, nostalgia, rebellion, jaded, desperation, escapism and confusion.

As the researchers say, there’s no guarantee of a marketing success with particular music but you may be able to better you odds.

David H. Henard and Christian L. Rossetti. All You Need is Love? Communication Insights from Pop Music’s Number-One Hits. Journal of Advertising Research, 2014 (in press) DOI: 10.2501/JAR-54-1-000-000.

You may have noticed that the DOI looks broken (because it is). So, grab a copy of the paper here.

You will have a lot of fun reading this article, particularly the tables of words and themes.

It doesn’t mention Jimi Hendrix so now you know why I don’t work in marketing. 😉

March 15, 2014

How Gmail Onboards New Users

Filed under: Advertising,Marketing — Patrick Durusau @ 9:28 pm

How Gmail Onboards New Users

From the post:

After passing Hotmail in 2012 as the world’s #1 email service with a sorta-impressive 425 million users(!), it can only be assumed that they’ve grown in the years since. Wanna see how it’s done in Gmail town?

A great set of sixty-nine (69) slides that point out how GMail has treated new users.

In a short phrase: Better than anyone else. (full stop)

You may have the “best” solution or the lower cost solution or whatever. If you don’t get users to stay long enough to realize that, well, you will soon be doing something else.

GMail’s approach won’t work as a cookie-cutter design for you but lessons can be adapted.

I first saw this in a tweet by Fabio Catapano

March 12, 2014

What do policymakers want from researchers?…

Filed under: Government,Marketing,Topic Maps — Patrick Durusau @ 2:20 pm

What do policymakers want from researchers? Blogs, elevator pitches and good old fashioned press mentions. by Duncan Green.

From the post:

Interesting survey of US policymakers in December’s International Studies Quarterly journal. I’m not linking to it because it’s gated, thereby excluding more or less everyone outside a traditional academic institution (open data anyone?) but here’s a draft of What Do Policymakers Want From Us?, by Paul Avey and Michael Desch. The results are as relevant to NGO advocacy people trying to influence governments as they are to scholars. Maybe more so. I’ve added my own running translation.

Two tidbits to get you interested in the report:

First, unclassified newspaper articles were as important to policymakers as the classified information generated inside the government.

[role of scholars] The main contribution of scholars, in their view, was research. Second, and again somewhat surprisingly, they expressed a preference for scholars to produce “arguments” (what we would call theories) over the generation of specific “evidence” (what we think of as facts). In other words, despite their jaundiced view of cutting-edge tools and rarefied theory, the thing policymakers most want from scholars are frameworks for making sense of the world they have to operate in.’

While the article focuses on international relations, I suspect the same attitudes hold true for other areas as well.

The impact of newspaper articles suggests that marketing semantic technologies at geek conferences isn’t the road to broad success.

As for making sense of the world, topic maps support frameworks with that result but not without effort.

Perhaps a topic map-based end product that is such a framework would be a better product?

I first saw this in a tweet by Coffeehouse.

March 7, 2014

Who Are the Customers for Intelligence?

Filed under: Intelligence,Marketing — Patrick Durusau @ 8:37 pm

Who Are the Customers for Intelligence? by Peter C. Oleson.

From the paper:

Who uses intelligence and why? The short answer is almost everyone and to gain an advantage. While nation-states are most closely identified with intelligence, private corporations and criminal entities also invest in gathering and analyzing information to advance their goals. Thus the intelligence process is a service function, or as Australian intelligence expert Don McDowell describes it,

Information is essential to the intelligence process. Intelligence… is not simply an amalgam of collected information. It is instead the result of taking information relevant to a specific issue and subjecting it to a process of integration, evaluation, and analysis with the specific purpose of projecting future events and actions, and estimating and predicting outcomes.

It is important to note that intelligence is prospective, or future oriented (in contrast to investigations that focus on events that have already occurred).

As intelligence is a service, it follows that it has customers for its products. McDowell differentiates between “clients” and “customers” for intelligence. The former are those who commission an intelligence effort and are the principal recipients of the resulting intelligence product. The latter are those who have an interest in the intelligence product and could use it for their own purposes. Most scholars of intelligence do not make this distinction. However, it can be an important one as there is an implied priority associated with a client over a customer. (footnote markers omitted)

If you want to sell the results of topic maps, that is highly curated data that can be viewed from multiple perspectives, this essay should spark your thinking about potential customers.

You may also find this website useful: Association of Former Intelligence Officers.

I first saw this at Full Text Reports as Who Are the Customers for Intelligence? (draft).

March 4, 2014

Parkinson’s Law, DevOps, and Kingdoms

Filed under: Marketing,Silos — Patrick Durusau @ 8:39 pm

Parkinson’s Law, DevOps, and Kingdoms by Michael Ducy.

From the post:

Destruction of silos is all the rage in DevOps and has been since the beginning of the movement. Patrick Debois wrote a very intelligent piece on why silos exist and how they came about as a management strategy. While the post explains why hierarchy style of management came about in the US (General Motors and Sloan), it doesn’t cover some of the personal motivations as to why silos or management kingdoms come about.

Michael and Patrick’s posts are very much worth your time if you want to market to organizations as they exist now and not as they may exist in some parallel universe.

For example, enabling managers to do more work with fewer staff is a sale plea that is DOA. Unless your offering will cut the staff of some corporate rival. (There are exceptions to every rule.)

Or, enabling a manager’s department to further the stated goals of the organization. The goal of managers are to further their departments, which may or may not be related to the mission of the organization.

Enjoy!

March 1, 2014

CrunchBase “semanticsearch”

Filed under: Marketing — Patrick Durusau @ 7:36 pm

CrunchBase “semanticsearch”

In a recent discussion of potential “semantic” products, I was pointed to the Crunchbase.com URL you see above.

Exploring the related tags and their related tags will give you an idea of potential competitors in a particular area.

Even more interesting is to do domain specific searches with your favorite search engine to see how many potential competitors are mentioned in mainstream business publications.

Or whatever market segment you have as a target for your service and/or software.

As opposed to geek literature.

I say that because the geek market is small in comparison to other market segments.

You can also use Crunchbase to identify companies that are successful in areas of interest so you can study their advertising and marketing strategies.

Their strategies will have to be adapted to fit your service/product but you can get a sense for what is likely to work.

In what innovative ways would you use Crunchbase to evaluate a market and/or develop marketing strategies?

February 24, 2014

I expected a Model T, but instead I got a loom:…

Filed under: BigData,Marketing — Patrick Durusau @ 2:37 pm

I expected a Model T, but instead I got a loom: Awaiting the second big data revolution by Mark Huberty.

Abstract:

Big data” has been heralded as the agent of a third industrial revolution{one with raw materials measured in bits, rather than tons of steel or barrels of oil. Yet the industrial revolution transformed not just how firms made things, but the fundamental approach to value creation in industrial economies. To date, big data has not achieved this distinction. Instead, today’s successful big data business models largely use data to scale old modes of value creation, rather than invent new ones altogether. Moreover, today’s big data cannot deliver the promised revolution. In this way, today’s big data landscape resembles the early phases of the first industrial revolution, rather than the culmination of the second a century later. Realizing the second big data revolution will require fundamentally di fferent kinds of data, diff erent innovations, and diff erent business models than those seen to date. That fact has profound consequences for the kinds of investments and innovations firms must seek, and the economic, political, and social consequences that those innovations portend.

From the introduction:

Four assumptions need special attention: First, N = all, or the claim that our data allow a clear and unbiased study of humanity; second, that today equals tomorrow, or the claim that understanding online behavior today implies that we will still understand it tomorrow; third, that understanding online behavior off ers a window into offine behavior; and fourth, that complex patterns of social behavior, once understood, will remain stable enough to become the basis of new data-driven, predictive products and services. Each of these has its issues. Taken together, those issues limit the future of a revolution that relies, as today’s does, on the \digital exhaust” of social networks, e-commerce, and other online services. The true revolution must lie elsewhere.

Mark makes a compelling case for most practices with “Big Data” are more of same, writ large, as opposed to something completely different.

Topic mappers can take heart from this passage:

Online behavior is a culmination of culture, language, social norms and other factors that shape both people and how they express their identity. These factors are in constant flux. The controversies and issues of yesterday are not those of tomorrow; the language we used to discuss anger, love, hatred, or envy change. The pathologies that afflict humanity may endure, but the ways we express them do not.

The only place where Mark loses me is in the argument that because our behavior changes, it cannot be predicted. Advertisers have been predicting human behavior long enough that they do miss, still, but they hit more than they miss.

Mark mentions Google but in terms of advertising, Google is the kid with a lemonade stand when compared to traditional advertisers.

One difference between Google advertising and traditional advertising is Google has limited itself to online behavior in constructing a model for its ads. Traditional advertisers measure every aspect of their target audience that is possible to measure.

Not to mention that traditional advertising is non-rational. That is traditional advertising will use whatever images, themes, music, etc., that has been shown to make a difference in sales. How that relates to the product or a rational basis for purchasing, is irrelevant.

If you don’t read any other long papers this week, you need to read this one.

Then ask yourself: What new business, data or technologies are you bringing to the table?

I first saw this in a tweet by Joseph Reisinger.

February 17, 2014

Ad for Topic Maps

Filed under: Data Governance,Federation,Marketing,Master Data Management,Topic Maps — Patrick Durusau @ 9:29 am

Imagine my surprise at finding an op-ed piece in Information Management flogging topic maps!

Karen Heath writes in: Is it Really Possible to Achieve a Single Version of Truth?:

There is a pervasive belief that a single version of truth–eliminating data siloes by consolidating all enterprise data in a consistent, non-redundant form – remains the technology-equivalent to the Holy Grail. And, the advent of big data is making it even harder to realize. However, even though SVOT is difficult or impossible to achieve today, beginning the journey is still a worthwhile business goal.

The road to SVOT is paved with very good intentions. SVOT has provided the major justification over the past 20 years for building enterprise data warehouses, and billions of dollars have been spent on relational databases, ETL tools and BI technologies. Millions of resource hours have been expended in construction and maintenance of these platforms, yet no organization is able to achieve SVOT on a sustained basis. Why? Because new data sources, either sanctioned or rogue, are continually being introduced, and existing data is subject to decay of quality over time. As much as 25 percent of customer demographic data, including name, address, contact info, and marital status changes every year. Also, today’s data is more dispersed and distributed and even “bigger” (volume, variety, velocity) than it has ever been.
…

Karen does a brief overview of why so many SVOT projects have failed (think lack of imagination and insight for starters) but then concludes:

As soon as MDM and DG are recognized as having equal standing with other programs in terms of funding and staffing, real progress can be made toward realization of a sustained SVOT. It takes enlightened management and a committed workforce to understand that successful MDM and DG programs are typically multi-year endeavors that require a significant commitment to of people, processes and technology. MDM and DG are not something that organizations should undertake with a big-bang approach, assuming that there is a simple end to a single project. SVOT is no longer dependent on all data being consolidated into a single physical platform. With effective DG, a federated architecture and robust semantic layer can support a multi-layer, multi-location, multi-product organization that provides its business users the sustained SVOT. That is the reward. (emphasis added)

In case you aren’t “in the know,” DG – data governance, MDM – master data management, SVOT – single version of truth.

The bolded line about the “robust semantic layer” is obviously something topic maps can do quite well. But that’s not where I saw the topic map ad.

I saw the topic map ad being highlighted by:

As soon as MDM and DG are recognized as having equal standing with other programs in terms of funding and staffing

Because that’s never going to happen.

And why should it? GM for example has legendary data management issues but their primary business, MDM and DG people to one side, is making and financing automobiles. They could divert enormous resources to obtain an across the board SVOT but why?

Rather than across the board SVOT, GM is going to want a more selective, a MVOT (My Version Of Truth) application. So it can be applied where it returns the greatest ROI for the investment.

With topic maps as “a federated architecture and robust semantic layer [to] support a multi-layer, multi-location, multi-product organization,” then accounting can have its MVOT, production its MVOT, shipping its MVOT, management its MVOT, regulators their MVOT.

Given the choice between a Single Version Of Truth and your My Version Of Truth, which one would you choose?

That’s what I thought.

PS: Topics maps can also present a SVOT, just in case its advocates come around.

February 7, 2014

Self-promotion for game developers

Filed under: Interface Research/Design,Marketing — Patrick Durusau @ 3:38 pm

Self-promotion for game developers by Raph Koster.

From the post:

I’m writing this for Mattie Brice, who was just listed as one of Polygon’s 50 game newsmakers of the year.

We had a brief Twitter exchange after I offered congratulations, in which she mentioned that she didn’t know she could put this on a CV, and that she “know[s] nothing of self-promotion.” I have certainly never been accused of that, so this is a rehash of stuff I have written elsewhere and elsewhen.

To be clear, this post is not about marketing your games. It is about marketing yourself, and not even that, but about finding your professional place within the industry.

Ralph’s advice is applicable to any field. Read it but more than that, take it to heart.

While you are there, take a look at: Theory of Fun for Game Design by Raph Koster.

There are no rules that say topic map applications have to be drudgery.

I first saw this in a tweet by Julia Evans.

February 3, 2014

Features vs. Benefits

Filed under: Marketing — Patrick Durusau @ 9:22 pm

Features vs. Benefits

This is an except from a book on “User Onboarding:”

onboarding

That has to be the best summary of sales strategy I have ever seen.

Visit the webpage and sign up for more information. This has a lot of promise.

BTW, substitute elected official for product and see what you think of your candidate’s rhetoric. 😉

February 2, 2014

Finding pi…

Filed under: Marketing,Topic Maps — Patrick Durusau @ 5:05 pm

Finding pi: Enterprises must dump their legacy ideas and search for radical innovation by Nirav Shah.

From the post:

Radical innovation has historically overcome barriers to scientific progress. For example, the discovery of pi as a numerical concept found application in mathematics, physics, signal and image processing, genomics and across domains. Similarly, the internet unleashed innovation across industries. Today, the computing world stands at a point where “pi”-like innovations can unlock quantum value.

The disproportionate dichotomy

Enterprises spend $2.7 trillion on technology related products. More than 95 percent of that spend is driven by desktop or laptop related applications, services, networking and data center infrastructure for employees, partners and customers.

Amongst enterprises, there is an installed base of 700 million personal computers, while smartphones and tablets form an installed base of 400 million mobile computing units. While mobile computing units constitute 36 percent of devices, less than 5 percent of enterprise dollars are focused on the mobile device base highlighting a disproportionate dichotomy.

Nirav’s article is an interesting read but I’m not sure we should be seeking a “pi” moment.

There is evidence of π being known since approximately 1900 to 1600 BCE. Which means it has taken 3,600+ years for π to embed itself in society. I suspect investors would like a somewhat faster return on their investment.

But we don’t need a π moment to make that happen. Consider this observation from Nirav’s post:

A survey of CIOs indicate that more than two thirds of North American and European insurers will increase investment in mobile applications, however Gartner predicts that lack of alignment with customer interests and poor technical execution will lead to low adoption rates. In fact, Gartner expects that by 2016 more than 50 percent of the mobile insurance customer apps will be discontinued.

Does the Gartner stat surprise you?

How often have you sat at a basketball game wishing you could check on your automobile insurance policy?

Software apps that are born of or sustained by management echo chambers are going to fail.

There is nothing surprising or alarming about their fate.

What is alarming, at least to a degree, is that successful apps are identified after the fact of their success. Having a better model for what successful apps share in common, might increase the odds of having future successful apps.

Pointers anyone?

PS: Of course I am thinking of this in terms of topic map apps.

Assuming that a topic map can semantically integrate across languages to return 300 papers for a search instead of 200, where is the bang for me in that result? The original result was too high to be useful to me. How does having more results help?

January 21, 2014

…Desperately Seeking Data Integration

Filed under: Data Integration,Government,Government Data,Marketing,Topic Maps — Patrick Durusau @ 8:30 pm

Why the US Government is Desperately Seeking Data Integration by David Linthicum.

From the post:

“When it comes to data, the U.S. federal government is a bit of a glutton. Federal agencies manage on average 209 million records, or approximately 8.4 billion records for the entire federal government, according to Steve O’Keeffe, founder of the government IT network site, MeriTalk.”

Check out these stats, in a December 2013 MeriTalk survey of 100 federal records and information management professionals. Among the findings:

  • Only 18 percent said their agency had made significant progress toward managing records and email in electronic format, and are ready to report.
  • One in five federal records management professionals say they are “completely prepared” to handle the growing volume of government records.
  • 92 percent say their agency “has a lot of work to do to meet the direction.”
  • 46 percent say they do not believe or are unsure about whether the deadlines are realistic and obtainable.
  • Three out of four say the Presidential Directive on Managing Government Records will enable “modern, high-quality records and information management.”

I’ve been working with the US government for years, and I can tell that these facts are pretty accurate. Indeed, the paper glut is killing productivity. Even the way they manage digital data needs a great deal of improvement.

I don’t doubt a word of David’s post. Do you?

What I do doubt is the ability of the government to integrate its data. At least unless and until it makes some fundamental choices about the route it will take to data integration.

First, replacement of existing information systems is a non-goal. Unless that is an a prioriassumption, the politics, both on Capital Hill and internal to any agency, program, etc. will doom a data integration effort before it begins.

The first non-goal means that the ROI of data integration must be high enough to be evident even with current systems in place.

Second, integration of the most difficult cases is not the initial target for any data integration project. It would be offensive to cite all the “boil the ocean” projects that have failed in Washington, D.C. Let’s just agree that judicious picking of high value and reasonable effort integration cases are a good proving ground.

Third, the targets and costs for meeting those targets of data integration, along with expected ROI, will be agreed upon by all parties before any work starts. Avoidance of mission creep is essential to success. Not to mention that public goals and metrics will enable everyone to decide if the goals have been meet.

Fourth, employment of traditional vendors, unemployed programmers, geographically dispersed staff, etc. are also non-goals of the project. With the money that can be saved by robust data integration, departments can feather their staffs as much as they like.

If you need proof of the fourth requirement, consider the various Apache projects that are now the the underpinnings for “big data” in its many forms.

It is possible to solve the government’s data integration issues. But not without some hard choices being made up front about the project.

Sorry, forgot one:

Fifth, the project leader should seek a consensus among the relevant parties but ultimately has the authority to make decisions for the project. If every dispute can have one or more parties running to their supervisor or congressional backer, the project is doomed before it starts. The buck stops with the project manager and no where else.

January 18, 2014

Coding books should be stories first…

Filed under: Marketing,Topic Maps — Patrick Durusau @ 10:31 am

I saw this in a tweet by Jordan Leigh:

Coding books should be stories first, and just happen to be about code. Instead we have coding docs that just happen to be in a book form.

Looking back over topic map presentations, papers, books, etc., did we also fall into that trap?

It’s rubs the wrong way to have spend so much time on obscure issues only to have to ignore them to talk about what interests users. 😉

What user stories do you think are the most interesting?

The only way to test starting from users stories is to start with user stories. Quite possibly fleshing out the user story and issues before even mentioning topic maps.

Sort of like the fiction writing advice to “start with chapter two.” The book I have in mind recommended that you start with some sort of crisis, emergency, etc. Get readers interested in the character before getting into background details.

Perhaps that approach would work for topic maps.

For all the “solutions” for Big Data, I have yet to see one that addresses the semantic needs of “Big Data.”

You?

January 15, 2014

Marin’s Year on SlideShare

Filed under: Communication,Marketing — Patrick Durusau @ 7:24 pm

Marin’s Year on SlideShare

Marin Dimitrov tweeted today:

SlideShare says my content is among the top 1% of most viewed on SlideShare in 2013

Since I am interested in promoting topic maps and SlideShare is a venue for that, I checked the Slideshare summary, looking for clues.

First, Marin hasn’t overloaded SlideShare, some 14 slideshares to date.

Second, none of the slideshares with high ratings are particularly recent (2010).

Third, 19.5 slides per presentation against the average of 14.4.

Fourth, average words per slide, 35.4 compared to average slideshare of 10.

Is that the magic bullet?

We have all been told to avoid “death by powerpoint.”

There is a presentation with that name: Death by PowerPoint (and how to fight it) by Alexei Kapterev. (July 31, 2007)

Great presentation but at slide 40 Alexei says:

People read faster than you speak. This means you are useless.

(written over a solid text background)

How to explain Marin’s high amount of text versus Alexei saying to not have much text?

Marin’s NoSQL Databases, most of the sixty (60) slides are chock full of text. Useful text to be sure but very full of it.

My suspicion is that what works for a presentation to a live audience, were you can fill out the points, explain pictures, etc., isn’t the same thing as a set of slides for readers who didn’t see the floor show.

Readers who didn’t hear the details are likely to find “great” slides for a live presentation to be too sparse to be useful.

So my working theory is that slides for live presentations should be quite different from slides for posting to Slideshare. What can be left for you to ad lib for the live audience should be spelled out on the slides. (my working hypothesis)

Suggestions/comments?

PS: I intend to test this theory with some slides on topic maps at the end of January.

January 7, 2014

Unaccountable:…

Filed under: Finance Services,Marketing,Topic Maps — Patrick Durusau @ 7:19 pm

Unaccountable: The high cost of the Pentagon’s bad bookkeeping.

Part 1: Number Crunch by by Scot J. Paltrow and Kelly Carr (July 2, 2013)

Part 2: Faking It. by Scot J. Paltrow (November 18, 2013)

Part 3: Broken Fixes by Scot J. Paltrow (December 23, 2013)

If you imagine NSA fraud as being out of control, you haven’t seen anything yet.

Stated bluntly, bad bookkeeping by the Pentagon has a negative impact on its troops, its ability to carry out its primary missions and is a sinkhole for taxpayer dollars.

If you make it to the end of Part 3, you will find:

  • The Pentagon was required to be auditable by 1996 (with all other federal agencies). The current, largely fictional deadline is 2017.
  • Since 1996, the Pentagon has spent an unaudited $8.5 trillion.
  • The Pentagon may have as many as 5,000 separate accounting systems.
  • Attempts to replace Pentagon accounting systems have been canceled after expenditures of $1 billion on more than one, as failures.
  • There are no legal consequences for the Pentagon, the military services, their members or civilian contractors if the Pentagon fails to meet audit deadlines.

If external forces were degrading the effectiveness of the U.S. military to this degree, Congress would be hot to fix the problem.

Topic maps aren’t a complete answer to this problem but they could help with the lack of accountability for the problem. Every order originates with someone approving it. Topic maps could bind that order to a specific individual and track its course through whatever systems exist today.

A running total of unaudited funds would be kept for every individual who approved an order. If those funds cannot be audited within say 90 days of the end of the fiscal year, that a lien is placed against any and all benefits they have accrued to that point. And everyone higher than themselves in the chain of command. To give commanders “skin in the game.”

Tracking of responsibility and not the funds, with automatic consequences for failure, would provide incentives for the Pentagon to improve the morale of its troops, to improve its combat readiness and to be credible when asking the Congress and American pubic for additional funds for specific purposes.

Do you have similar problems at your enterprise?

January 5, 2014

What “viable search engine competition” really looks like

Filed under: Marketing,Search Analytics,Search Engines,Search Requirements — Patrick Durusau @ 3:56 pm

What “viable search engine competition” really looks like by Alex Clemmer.

From the post:

Hacker News is up in arms again today about the RapGenius fiasco. See RapGenius statement and HN comments. One response article argues that we need more “viable search engine competition” and the HN community largely seems to agree.

In much of the discussion, there is a picaresque notion that the “search engine problem” is really just a product problem, and that if we try really hard to think of good features, we can defeat the giant.

I work at Microsoft. Competing with Google is hard work. I’m going to point out some of the lessons I’ve learned along the way, to help all you spry young entrepreneurs who might want to enter the market.

Alex has six (6) lessons for would-be Google killers:

Lesson 1: The problem is not only hiring smart people, but hiring enough smart people.

Lesson 2: competing on market share is possible; relevance is much harder

Lesson 3: social may pose an existential threat to Google’s style of search

Lesson 4: large companies have access to technology that is often categorically better than OSS state of the art

Lesson 5: large companies are necessarily limited by their previous investments

Lesson 6: large companies have much more data than you, and their approach to search is sophisticated

See Alex’s post for the details under each lesson.

What has always puzzled me is why compete on general search? General search services are “free” save for the cost of a users time to mine the results. It is hard to think of a good economic model to compete with “free.” Yes?

If we are talking about medical, legal, technical, engineering search, where services are sold to professionals and the cost is passed onto consumers, that could be a different story. Even there, costs have to be offset by a reasonable expectation of profit against established players in each of those markets.

One strategy would be to supplement or enhance existing search services and pitch that to existing market holders. Another strategy would be to propose highly specialized searching of unique data archives.

Do you think Alex is right in saying “…most traditional search problems have really been investigated thoroughly”?

I don’t because of the general decline in information retrieval from the 1950’s-1960’s to date.

If you doubt my observation, pick a Readers’ Guide to Periodical Literature (hard copy) for 1968 and choose some subject at random. Repeat that exercise with the search engine of your choice, limiting your results to 1968.

Which one gave you more relevant references for 1968, including synonyms? Say in the first 100 entries.

I first saw this in a tweet by Stefano Bertolo.

PS: I concede that the analog book does not have digital hyperlinks to take you to resources but it does have analog links for the same purpose. And it doesn’t have product ads. 😉

January 3, 2014

How to Give a Killer Presentation

Filed under: Marketing,Presentation — Patrick Durusau @ 3:58 pm

How to Give a Killer Presentation by Chris Anderson.

As the curator of the TED conference since 2002, Chris is no stranger to great presentations!

In How to Give a Killer Presentation (viewing is free but requires registration), he gives a synopsis of what to do and just as importantly, what not to do for a “killer” presentation.

Whether you are presenting a paper on topic maps at a conference, making a presentation to a class or to a small group of decision makers, you will benefit from the advice that Chris has in this article.

None of the advice is new but compare the conference presentations you have seen to any good TED talk. See what I mean?

Don’t neglect Chris’ advice if you are preparing videos. Keeping an audience engaged is even harder when a presentation isn’t “live.”

I first saw this at: How to give a killer talk by Chris Crockett. That is a post at an astronomy blog trying to improve presentations at astronomy conferences.

The concerns of topic mappers may seem unique to us but for the most part, they are shared across disciplines.

January 2, 2014

Standards

Filed under: Humor,Marketing,Topic Maps — Patrick Durusau @ 5:05 pm

standards

Standards proliferation is driven by standards organizations, their staffs, their members and others.

Topic maps can’t stop the proliferation of standards any more than endless ontology discussions will result in a single ontology.

Topic maps can provide one or more views of a mapping between standards.

Views to help you transition between standards or to produce data serialized according to different standards.

December 25, 2013

The 25 Biggest Brand Fails of 2013

Filed under: Advertising,Marketing,Topic Maps — Patrick Durusau @ 3:11 pm

The 25 Biggest Brand Fails of 2013 by Tim Nudd.

From the post:

Arrogant, intolerant, sexist, disgusting, cheesy, tasteless, just plain stupid. Brand fails come in all kinds of off-putting shapes and sizes, though one thing remains constant—the guilty adrenaline rush of ad-enfreude that onlookers feel while watching brands implode for everyone to see.

We’ve collected some of the most delectably embarrassing marketing moments from 2013 for your rubbernecking pleasure. Eat it up, you heartless pigs. And just be thankful it wasn’t you who screwed up this royally.

Amusing but also lessons in what not to do when advertising topic maps.

Another approach that doesn’t work is “…why isn’t everybody migrating to technology X? It’s so great….”

I kid you not. The video seemed to go on forever.

The video missed what many of the 25 ads missed, it’s a two part test for effective advertising:

  1. What’s in it for the customer?
  2. Is the “what” something the customer cares about?

If you miss either one of those points, the ad is a dud even if it doesn’t make the top 25 poorest ads next year.

December 21, 2013

Google Transparency Report

Filed under: Marketing,Search Behavior,Search Data,Search History,Transparency — Patrick Durusau @ 5:32 pm

Google Transparency Report

The Google Transparency Report consists of five parts:

  1. Government requests to remove content

    A list of the number of requests we receive from governments to review or remove content from Google products.

  2. Requests for information about our users

    A list of the number of requests we received from governments to hand over user data and account information.

  3. Requests by copyright owners to remove search results

    Detailed information on requests by copyright owners or their representatives to remove web pages from Google search results.

  4. Google product traffic

    The real-time availability of Google products around the world, historic traffic patterns since 2008, and a historic archive of disruptions to Google products.

  5. Safe Browsing

    Statistics on how many malware and phishing websites we detect per week, how many users we warn, and which networks around the world host malware sites.

I pointed out the visualizations of the copyright holder data earlier today.

There are a number of visualizations of the Google Transparency Report and I may assemble some of the more interesting ones for your viewing pleasure.

You certainly should download the data sets and/or view them as Google Docs Spreadsheets.

I say that because while Google is more “transparent” than the current White House, it’s not all that transparent at all.

Take the government take down requests for example.

According to the raw data file, the United States has made five (5) requests on the basis of national security, four (4) of which were for YouTube videos and one (1) was for one web search result.

Really?

And for no government request, is there sufficient information to identify the information that any government sought to conceal.

Google may have qualms about information governments want to conceal but that sounds like a marketing opportunity to me. (Being mindful of your availability to such governments.)

December 14, 2013

Is Nothing Sacred?

Filed under: Games,Marketing,Topic Maps — Patrick Durusau @ 5:35 pm

Podcast: Spying with Avatars by Nicole Collins Bronzan.

From the post:

As we reported with The New York Times this week, American and British spies have infiltrated online fantasy games, thinking them ripe for use by militants. Justin Elliott joins Stephen Engelberg in the Storage Closet Studio this week to talk about avatars, spies, and the punchline-inspiring intersection of the two.

As shown in the documents leaked from former National Security Agency contractor Edward J. Snowden to The Guardian, the NSA and its British counterpart, Government Communications Headquarters, have created make-believe characters to snoop and to try to recruit informers, while also collecting data and contents of communications between players, who number in the millions across the globe.

The intelligence community is so invested in this new arena, Elliott reports, that they needed a “deconfliction” group to solve redundancies as spies from many agencies bumped into each other in “Second Life.”

But that enthusiasm is not necessarily unfounded.

“One thing that I found — in the course of my reporting — that I found really interesting was a survey from this period when the games were getting very popular that found something around 30 percent of people who played these games and responded in this survey, by an academic researcher, said that they had shared personal information or secrets with their friends within the game that they had never shared with their friends in the real world,” Elliott says. “So I think we can all have sort of a few laughs about this, but for some people, these games really can function as sort of private spaces, which why I think, in part, the documents raise questions about privacy and legality of what the agencies were doing.”

How could anyone agree to infiltrate an online game?

I can understand rendering, torture, assassinations, bribery, lying, ignoring domestic and international law, to say nothing of the Constitution of the United States. Those are routine functions of government. Have been for all of my life.

But infiltrating online games, the one refuge from government malfeasance and malice many people have. That’s just going one step too far.

Gamers need to fight back! Track everyone you come in contact with. Track their questions, who they know, who they are with, etc.

Not all of them will openly ask you if you want to borrow a car bomb? That’s a dead tip-off that you dealing with the FBI.

Government agents are as trackable (perhaps more so) as anyone else. Enlist game management. Start games the government will want to infiltrate.

Track them in your world, so you can remonstrate with public officials in theirs.

PS: Topic maps are a good solution to tracking individuals across avatars and games. And they don’t require a melting data center to run. 😉

December 9, 2013

Quandl exceeds 7.8 million datasets!

Filed under: Data,Dataset,Marketing — Patrick Durusau @ 9:01 am

From The R Backpages 2 by Joseph Rickert.

From the post:

Quandl contiues its mission to seek out and make available the worlds financial and econometric data. Recently added data sets include:

That’s a big jump since our last post when Quandl broke 5 million datasets! (April 30, 2013)

Any thoughts on how many of these datasets have semantic mapping data to facilitate their re-use and/or combination with other datasets?

Selling the mapping data might be a tough sell because the customer still has to make intelligent use of it.

Selling mapped data on the other hand, that is offering consolidation of specified data sets on a daily, weekly, monthly basis, that might be a different story.

Something to think about.

PS: Do remember that a documented mapping for any dataset at Quandl will work for that same dataset elsewhere. So you won’t be re-discovering the mapping every time a request comes in for that dataset.

Not a “…butts in seats…” approach but then you probably aren’t a prime contractor.

December 6, 2013

…: Selling Data

Filed under: Data,Marketing — Patrick Durusau @ 8:02 pm

A New Source of Revenue for Data Scientists: Selling Data by Vincent Granville.

From the post:

What kind of data is salable? How can data scientists independently make money by selling data that is automatically generated: raw data, research data (presented as customized reports), or predictions. In short, using an automated data generation / gathering or prediction system, working from home with no boss and no employee, and possibly no direct interactions with clients. An alternate career path that many of us would enjoy!

Vincent gives a number of examples of companies selling data right now, some possible data sources, startup ideas and pointers to articles on data scientists.

Vincent makes me think there are at least three ways to sell topic maps:

  1. Sell people on using topic maps so they can produce high quality data through the use of topic maps.
  2. Sell people on hiring you to construct a topic map system so they can produce high quality data.
  3. Sell people high quality data because you are using a topic map.

Not everyone who likes filet mignon (#3), wants to raise the cow (#1) and/or butcher the cow(#2).

It is more expensive to buy filet mignon, but it also lowers the odds of stepping in cow manure and/or blood.

What data would you buy?

December 4, 2013

MusicGraph

Filed under: Graphs,Marketing,Music,Titan — Patrick Durusau @ 4:30 pm

Senzari releases a searchable MusicGraph service for making musical connections by Josh Ong.

From the post:

Music data company Senzari has launched MusicGraph, a new service for discovering music by searching through graph of over a billion music-related data points.

MusicGraph includes a consumer-facing version and an API that can be used for commercial purposes. Senzari built the graph while working on the recommendation engine for its own streaming service, which has been rebranded as Wahwah.

Interestingly, MusicGraph is launching first on Firefox OS before coming to iOS, Android and Windows Phone in “the coming weeks.”

You know how much I try to avoid “practical” applications but when I saw aureliusgraphs tweet this as using the Titan database, I just had to mention it. 😉

I think this announcement underlines something a comment said recently about promoting topic maps for what they do, not because they are topic maps.

Here, graphs are being promoted as the source of a great user experience, not because they are fun, powerful, etc. (all of which is also true).

November 22, 2013

DataCleaner 3.5.7 released

Filed under: DataCleaner,Deduplication,Marketing,Topic Maps — Patrick Durusau @ 4:31 pm

DataCleaner 3.5.7 released

A point release but I haven’t mentioned DataCleaner since before version 2.4. Sorry.

True, DataCleaner doesn’t treat all information structures as subjects, etc., but then you don’t need a topic map for every data handling job.

Opps! I don’t think I was supposed to say that. 😉

Seriously, you need to evaluate every data technology and/or tool on the basis of your requirements.

Topic maps included.

November 20, 2013

Big Data: Main Research/Business Challenges Ahead?

Filed under: Findability,Integration,Marketing,Personalization,Searching — Patrick Durusau @ 7:13 pm

Big Data Analytics at Thomson Reuters. Interview with Jochen L. Leidner by Roberto V. Zicari.

In case you don’t know, Jochen L. Leidner has the title: “Lead Scientist, of the London R&D at Thomson Reuters.”

Which goes a long way to explaining the importance of this Q&A exchange:

Q12 What are the main research challenges ahead? And what are the main business challenges ahead?

Jochen L. Leidner: Some of the main business challenges are the cost pressure that some of our customers face, and the increasing availability of low-cost or free-of-charge information sources, i.e. the commoditization of information. I would caution here that whereas the amount of information available for free is large, this in itself does not help you if you have a particular problem and cannot find the information that helps you solve it, either because the solution is not there despite the size, or because it is there but findability is low. Further challenges include information integration, making systems ever more adaptive, but only to the extent it is useful, or supporting better personalization. Having said this sometimes systems need to be run in a non-personalized mode (e.g. in the field of e-discovery, you need to have a certain consistency, namely that the same legal search systems retrieves the same things today and tomorrow, and to different parties.

How are you planning to address:

  1. The required information is not available in the system. A semantic 404 as it were. To distinguish the case of its there but wrong search terms in use.
  2. Low findability.
  3. Information integration (not normalization)
  4. System adaptability/personalization, but to users and not developers.
  5. Search consistency, same result tomorrow as today.

?

The rest of the interview is more than worth your time.

I singled out the research/business challenges as a possible map forward.

We all know where we have been.

Casualty Count for Obamacare (0)

Filed under: Advertising,Government,Government Data,Health care,Marketing — Patrick Durusau @ 3:08 pm

5 lessons IT leaders can learn from Obamacare rollout mistakes by Teena Hammond.

Teena reports on five lessons to be learned from the HealthCare.gov rollout:

  1. If you’re going to launch a new website, decide whether to use in-house talent or outsource. If you opt to outsource, hire a good contractor.
  2. Follow the right steps to hire the best vendor for the project, and properly manage the relationship.
  3. Have one person in charge of the project with absolute veto power.
  4. Do not gloss over any problems along the way. Be open and honest about the progress of the project. And test the site.
  5. Be ready for success or failure. Hope for the best but prepare for the worst and have guidelines to manage any potential failure.

There is a sixth lesson that emerges from Vaughn Bullard, CEO and founder of Build.Automate Inc., who is quoted in part saying:

The contractor telling the government that it was ready despite the obvious major flaws in the system is just baffling to me. If I had an employee that did something similar, I would have terminated their employment. It’s pretty simple.”

What it comes down to in the end, Bullard said, is that, “Quality and integrity count in all things.”

To avoid repeated failures in the future (sixth lesson), terminate those responsible for the current failure.

All contractors and their staffs. Track the staffs in order to avoid the same staff moving to other contractors.

Termination all appointed or hired staff who responsible for the contract and/or management of the project.

Track former staff employment by contractors and refuse contracts wherever they are employed.

You may have noticed that the reported casualty count for the Obamacare failure has been zero.

What incentive exists for the next group of contract/project managers and/or contractors for “quality and integrity?”

That would be the same as the casualty count, zero.

PS: Before you protest the termination and ban of failures as cruel, consider its advantages as a wealth redistribution program.

The government may not get better service but it will provide opportunities for fraud and poor quality work from new participants.

Not to mention there are IT service providers who exhibit quality and integrity. Absent traditional mis-management, the government could happen upon one of those.

The tip for semantic technologies is to under-promise and over-deliver. Always.

HyperDex 1.0RC5

Filed under: Advertising,HyperDex,Marketing,NoSQL — Patrick Durusau @ 1:44 pm

HyperDex 1.0RC5 by Robert Escriva.

From the post:

We are proud to announce HyperDex 1.0.rc5, the next generation NoSQL data store that provides ACID transactions, fault-tolerance, and high-performance. This new release has a number of exciting features:

  • Improved cluster management. The cluster will automatically grow as new nodes are added.
  • Backup support. Take backups of the coordinator and daemons in a consistent state and be able to restore the cluster to the point when the backup was taken.
  • An admin library which exposes performance counters for tracking cluster-wide statistics relating to HyperDex
  • Support for HyperLevelDB. This is the first HyperDex release to use HyperLevelDB, which brings higher performance than Google’s LevelDB.
  • Secondary indices. Secondary indices improve the speed of search without the overhead of creating a subspace for the indexed attributes.
  • New atomic operations. Most key-based operations now have conditional atomic equivalents.
  • Improved coordinator stability. This release introduces an improved coordinator that fixes a few stability problems reported by users.

Binary packages for Debian 7, Ubuntu 12.04-13.10, Fedora 18-19, and CentOS 6 are available on the HyperDex Download page, as well as source tarballs for other Linux platforms.

BTW, HyperDex has a cool logo:

HyperDex

Good logos are like good book covers, they catch the eye of potential customers.

A book sale starts when a customer pick a book up, hence the need for a good cover.

What sort of cover does your favorite semantic application have?

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