Traditional Publishing versus Digital Flow
November 24, 2014
I read “Technology Set Journalism Free, Now New Platforms Are in Control.” I reacted positively to the word “platforms.” After I read the essay, I am not convinced that the platforms mentioned in the article are in control. These platforms have the appearance of control, but I think Facebook, Twitter, and other big consumer services have a flaw. The content streams can be manipulated, often easily. There are platforms that operate outside of the consumer sector. Some of these platforms are far more important than channels that disseminate content (either well intentioned or weaponized).
The challenge publishers who want to use print as a revenue generator and as a way to enforce information control on a customer segment face a number of challenges. The big one is figuring out how to make money as monopolies develop in various sectors. There are some interesting efforts to combine print and digital; for example, the Monocle operation. For most of the companies wanting to tap print’s unique power, the problems require clear thinking. When I have been asked to think about how to make print work, I extricate myself from that engagement. I am probably able to come up with useful ideas, but I want to spend my time working on more interesting problems.
The flaw in this write up and others that try to find a place in today’s world for certain approaches to information is cost. As soon as paper is involved, the expense of buying it, printing on it, shipping it, and delivering it are greater than the money most companies can generate by selling it. Without money, the companies accustomed to information control and its attendant power have a big job to do.
Niche outfits may be able to do okay. But the big companies dependent on print thinking are probably going to fall out of their leather chairs.
And what about the platforms that most do not see or do not seek out? These will continue to expand their reach, scope, and capabilities. When cheerleaders for Facebook and similar companies wake up, another paradigm shift will be well underway.
What’s interesting is that today’s new platforms will be facing the challenges print publishers deal with today.
Stephen E Arnold, November 24, 2014
Google: More Details on Mobile Devices
November 24, 2014
I read “Google Adds Detailed Info to Shopping Search Results on Mobile Devices.” Google has plenty of information about products if any of the Ramanathan Guha data structures have been put in place. The write up says:
Starting this week, mobile users searching for products on Google will see detailed information, specs, store availability and customer reviews. In addition, select products on Google Shopping will also have 360-degree views for a closer look.
Are these listings ads? I know that when I use my mobile devices to log into Google I often have to fiddle around to get what I call the classic desktop presentation. Google seems to have some difficulty figuring out what to put in front of users.
More on a mobile device can be problematic. I was looking for the street on which I lived in Brazil using my eye pad. I could not find a way to get around the information shoehorned on a limited viewing space.
Mobile is creating some online ad revenue challenges for Google. If more information crowds out ads, I ask, “Maybe the more information is a paid listing?” The write up does not provide any information to help me answer my questions.
I long for the good old days of Froogle and the catalog service. Call me a dinosaur.
Stephen E Arnold, November 24, 2014
Online Accuracy: The Hollywood Sign Approach
November 24, 2014
I read “Why People Keep Trying to Erase the Hollywood Sign from Google Maps.” The write up underscores the fluidity of the notion about accurate online information. Last time I was in Hollywood, I gave my talk at an intel conference and beat a quick path back to Kentucky. For those who think that life has not been lived until one stands at the base of a giant letter, Google Maps, if the write up is correct, may give you an extra workout. Here’s the passage I noted:
Even though Google Maps clearly marks the actual location of the sign, something funny happens when you request driving directions from any place in the city. The directions lead you to Griffith Observatory, a beautiful 1920s building located one mountain east from the sign, then—in something I’ve never seen before, anywhere on Google Maps—a dashed gray line arcs from Griffith Observatory, over Mt. Lee, to the sign’s site. Walking directions show the same thing.
Obviously in the world of online this is the only instance of information being modified so it does not match reality. I am comforted unlike some folks.
Stephen E Arnold, November 24, 2014
Make Your Own Metadata Webinar
November 24, 2014
Here is a unique idea that we have not heard about: “Build Your Own Canto Metadata Webinar.” Canto is a company that specializes in digital asset management and their award-winning Cumulus software is an industry favorite to manage taxonomies and metadata for digital content. People often forget how important metadata is Web content:
“Metadata lets you do more with your digital content.
Metadata can save you from copyright lawsuits.
Metadata can speed your everyday workflow.”
The webinar is advertised as way to help people understand what exactly metadata is, how people can harness it to their advantage, and how to engage more people into using it. While anyone can teach a webinar about metadata, Canto is building the entire session around users’ questions. They will be able to tweet questions before and during the meeting.
The webinar is led by three metadata experts: Thomas Schleu-CTO/Co-Founder of Canto, Phoenix Von Lieven-Director of Professional Services, Americas Cantos, and Danielle Forshtay-Publications Coordinator of Lockheed Martin. These experts will lend their knowledge to attendees.
“Build Your Own Canto Webinar” is an odd way to advertise an online class about metadata. Why is it called make your own? Are the attendees shaping the class’ content entirely? It does bear further investigation by attending the webinar on November 19.
Whitney Grace, November 24, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
An Expert WAND Partnership
November 24, 2014
Data is messy and needs to be kept clean. Data on a large, enterprise scale is a nightmare to neat freaks, because without an organizational hierarchy it would take years to sift through. Wand Inc.’s corporate blog posted some exciting news, “Expert System And WAND Partner For A More Effective Management Of Enterprise Information.” WAND is known throughout big data as the leader in enterprise taxonomies, while Expert Systems is renowned for its semantic technology.
The goal of the partnership is to help enterprise systems make their data more findable, manage better client relationships, and decrease operational risks. While the partnership will affect enterprise systems overall, there are three main factors that will overhaul the enterprise content management process:
1 “Taxonomy selection: WAND offers the biggest library of out-of-the-box taxonomies available on the market today. By selecting one of the available sector specific taxonomies, customers can speed up significantly their implementation time without compromising their specific classification requirements.
2 Automatic Classification based on the selected taxonomy: once the customer chooses the taxonomy, Expert System makes a full set of tools available to define the semantic based categorization rules and the engine that enables the automatic categorization of all the enterprise content.
3 Native integration with the most common document and collaboration systems, including Microsoft SharePoint.”
WAND and Expert Systems’ combined forces will allow enterprise systems to make their data more findable. While the partnership is beneficial, it reads like most big data relationships. What makes it different, however, are the names attached.
Whitney Grace, November 24, 2014
Sponsored by ArnoldIT.com, developer of Augmentext
Elasticsearch Ups the Pressure on LucidWorks (Really?)
November 23, 2014
I am not too keen on videos. I prefer reading hard copies. I did find the video referenced in “Elasticsearch Uses Power of Community for Open Source Analytics” useful. My team and I are putting the finishing touches on a report that points out how enterprise search vendors have been leapfrogged by vendors rarely considered by mid tier consultants and the self appointed experts in search. The video drives home a simple point: Combining open source technologies delivers information access functions that are more useful to users than laundry lists, odd ball point and click suggested content, and confusing mash ups of information presented without context.
Why the reference to Lucid? One of the firm’s presidents had been involved with Jaspersoft, an open source analytics outfit. Despite this “inside track”, Elasticsearch has powered past Lucid, leaving that open source vendor struggling to reach parity with Elasticsearch. Elasticsearch itself faces challenges, but that’s the name of the game when keyword search is the keystone of a service. For now, Elasticsearch leaves competitors rushing to close the gap. By the way, this subject was the focal point of one of Dave Schubmehl’s IDC reports that surfed on my name. The juicy part about the “gap” was edited from my original write up. Nevertheless, the facts remain valid. Kudos to Elasticsearch.
Stephen E Arnold, November 23, 2014
Fake Content: SEO or Tenure Desperation
November 23, 2014
This morning I thought briefly about “Profanity Laced Academic Paper Exposes Scam Journal.” The Slashdot item comments about a journal write up filled with nonsense. The paper was accepted by the International Journal of Advanced Computer Technology. I have received requests for papers from similar outfits. I am not interested in getting on a tenure track. The notion of my paying someone to publish my writings does not resonate. I either sell my work or give it away in this blog or one of the others I have available to me.
The question in my mind ping ponged between two different ways to approach this “pay to say” situation.
First, the authors who are involved in academic pursuits: “Are these folks trying to get the prestige that comes from publishing in an academic journal?” My hunch is that the motivation is similar to the force that drives the fake data people.
Second, has the search engine optimization crowd infected otherwise semi-coherent individuals that a link—any link—is worth money?
Indexing systems have a spotty record of identifying weaponized, shaped, or distorted information. The fallback position for many vendors is that by processing large volumes of information, the outliers can be easily tagged and either ignored or disproved.
Sounds good. Does it work? Nope. The idea that open source content is “accurate” may be a false assumption. You can run queries on Bing, iSeek, Google, and Yandex for yourself. Check out information related to the Ebola epidemic or modern fighter aircraft. What’s correct? What’s hoo hah? What’s downright craziness? What’s filtered? Figuring out what to accept as close to the truth is expensive and time consuming. Not part of today’s business model in most organizations I fear.
Stephen E Arnold, November 23, 2014
Chasing Non Swimmers from the Data Lake
November 22, 2014
If you are one of the Big Data believers, you will find “Clearing Up Muddied Waters in the ‘Data Lakes’” a reminder about the plasticity of concepts and their connotations. The write up addresses a clever phrase used to describe a storage pool into which
You store raw data at its most granular level so that you can perform any ad-hoc aggregation at any time. The classic data warehouse and data mart approaches do not support this.
The write up points out that the original notion of a data lake has been prodded, stretched, and pulled. Not surprisingly, after the verbal chiropractic, data lake is just not its old self.
Who are the perpetrators of this conceptual improvement? A “real” journalist and—no big surprise—several Big Data experts laboring away at a mid tier consulting firm.
So what? The coiner of the phrase points me and other readers to the original write up about data lakes here. Worth revisiting? Will the “real” journalist or the mid tier consultants likely to read the source document? I would guess not.
Stephen E Arnold, November 22, 2014
The Future of the Web Is… Google
November 22, 2014
I read “The Future of the Web (According to Google).” I love cheerleaders. But cheerleaders are not the game unless the program is one of those fillers that ESPN airs at odd ball times. In a nutshell, the future is video and Google’s (for now) of quite specific programming methods.
Here’s the passage I noted:
It’s clear that Google cares deeply about improving the mobile web experience. Personally, I tend to believe that the native app pendulum has swung out about as far as it can, and in the next few years we’ll start seeing it swing back toward Web tech again. Native vs. web isn’t a zero-sum game. There will always be reasons to build web apps, there will always be reasons to build native apps. We’re heading toward a future, however, where some of the biggest reasons to build native on mobile are going to disappear. As a developer who loves the web, that’s exciting.
The only storm clouds in this vision of the future are:
- Erosion of Google’s desktop advertising model which is, I believe, based on the GoTo/Overture/Yahoo model and not Google’s inherent innovative engine
- Europe’s desire to regulate the company
- The company’s penchant for taking its eye off the here and now and gazing into a future chock full of Google toys
- Internal management issues which resulted in one Googler believing her life had ground to a halt along with Google Glass.
Stephen E Arnold, November 22, 2014
Suicide Sentiment Analysis
November 21, 2014
Short honk: The notion of figuring out something about the emotional payload of a message is interesting. If you are following developments in sentiment analysis, you may find “Emotion Detection in Suicide Notes Using Maximum Entropy Classification” interesting. Now what might be done to pipe the output of this analysis into a predictive analytics engine with access to deep user data?
Stephen E Arnold, November 21, 2014
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