Exogenous Complexity 4: SEO and Big Data
February 29, 2012
Introduction
In the interview with Dr. Linda McIsaac, founder of Xyte, Inc., I learned that new analytic methods reveal high-value insights about human behavior. You can read the full interview in my Search Wizards Speak series at this link. The method involves an approach called Xyting and sophisticated analytic methods.
One example of the type of data which emerge from the Xyte method are these insights about Facebook users:
- Consumers who are most in tune with the written word are more likely to use Facebook. These consumers are the most frequent Internet users and use Facebook primarily to communicate with friends and connect with family.
- They like to keep their information up-to-date, meet new people, share photos, follow celebrities, share concerns, and solve people problems.
- They like to learn about and share experiences about new products. Advertisers should key in on this important segment because they are early adopters. They lead trends and influence others.
- The population segment that most frequents Facebook has a number of characteristics; for example, showing great compassion for others, wanting to be emotionally connected with others, having a natural intuition about people and how to relate to them, adapting well to change, embracing technology such as the Internet, and enjoying gossip and messages delivered in story form and liking to read and write.
- Facebook constituents are emotional, idealistic and romantic, yet can rationalize through situations. Many do not need concrete examples in order to comprehend new ideas.
I am not into social networks. Sure, some of our for-free content is available via social media channels, but where I live in rural Kentucky yelling down the hollow works quite well.
I read “How The Era Of ‘Big-Data’ Is Changing The Practice Of Online Marketing” and came away confused. You should work through the text, graphs, charts, and lingo yourself. I got a headache because most of the data struck me as slightly off center from what an outfit like Xyte has developed. More about this difference in a moment.
The thrust of the argument is that “big data” is now available to those who would generate traffic to client Web sites. Big data is described as “a torrent of digital data.” The author continues:
large sets of data that, when mined, could reveal insight about online marketing efforts. This includes data such as search rankings, site visits, SERPs and click-data. In the SEO realm alone at Conductor, for example, we collect tens of terabytes of search data for enterprise search marketers every month.
Like most SEO baloney, there are touchstones and jargon aplenty. For example, SERP, click data, enterprise search, and others. The intent is to suggest that one can pay a company to analyze big data and generate insights. The insights can be used to produce traffic to a Web page, make sales, or produce leads which can become sales. In a lousy business environment, such promises appeal to some people. Like most search engine optimization pitches, the desperate marketer may embrace the latest and greatest pitch. Little wonder there are growing numbers of unemployed professionals who failed to deliver the sales their employer wanted. The notion of desperation marketing fosters a services business who can assert to deliver sales and presumably job security for those who hire the SEO “experts.” I am okay with this type of business, and I am indifferent to the hollowness of the claims.
What interests me is this statement:
From our vantage point at Conductor, the move to the era of big data has been catalyzed by several distinct occurrences:
- Move to Thousands of Keywords: The old days of SEO involved tracking your top fifty keywords. Today, enterprise marketers are tracking up to thousands of keywords as the online landscape becomes increasingly competitive, marketers advance down the maturity spectrum and they work to continuously expand their zone of coverage in search.
- Growing Digital Assets: A recent Conductor study showed universal search results are now present in 8 out of 10 high-volume searches. The prevalence of digital media assets (e.g. images, video, maps, shopping, PPC) in the SERPs require marketers to get innovative about their search strategy.
- Multiple Search Engines: Early days of SEO involved periodically tracking your rank on Google. Today, marketers want to expand not just to Yahoo and Bing, but also to the dozens of search engines around the world as enterprise marketers expand their view to a global search presence.
All the above factors combined mean there are significant opportunities for an increase in both the breadth and volume of data available to search professionals.
Effective communication, in my experience, is not measured in “thousands of key words”. The notion of expanding the “zone of coverage” means that meaning is diffused. Of course, the intent of the key words is not getting a point across. The goal is to get traffic, make sales. This is the 2112 equivalent of the old America Online carpet bombing of CD ROMs decades ago. Good business for CD ROM manufacturers, I might add. Erosion of meaning opens the door to some exogenous complexity excitement I assert.
Discover Point: Search Shows the Unseen
February 16, 2012
Discover Point comes at search and retrieval with the “automatically connect people with highly relevant information.” I find this interesting because it makes search into a collaborative type of solution. Different from a search enable application, Discover Point pops up a conceptual level. After all, who wants another app. When I need information, I usually end up talking to an informed individual.
Government Computer News reported on this approach in the write up “An Info and Expertise Concierge for the Office.” GCN perceives Discover Point as having a solution for the US government which “prevents agencies from constantly reinventing the wheel and instead helps users move forward with new tasks and projects…” This is an interesting marketing angle because it shifts from assertions that few understand such as semantics, ontologies, and facets.
GCN continues:
DiscoverPoint from Discover Technologies is designed to point users in the direction of the most relevant information and subject-matter experts within the shared platform environment. As your job focus changes, so do the searches that DiscoverPoint makes….But the really cool things start happening after you’ve been using the system for a while. As more personnel and documents relevant to what you are doing become available on the system, they will show up on your discovery page.
The idea of having a system “discover” information appeals to the GCN professionals giving Discover Point a test drive.
Discover Point is compatible with SharePoint, Microsoft’s ubiquitous content management, collaboration, search, and kitchen sink solution. Discover Point’s news release emphasizes that the firm’s approach in unique. See “Discover Point Software Selected Product of the Month by Government Computer News.” The Discover Point Web site picks up this theme:
Discover Technologies’ approach is truly unique, in that we do not require the manual creation of databases or MySites or other repositories to understand the needs of each and every user. We continuously analyze the content they dwell in, and establish an understanding of the users’ interests based on that content. Once this user understanding is gained, and this happens very quickly, then the proactive delivery of information and ‘people’ is enabled and the cost savings and quality benefits are realized.
Unique is a strong word. The word suggests to me something which is the only one of its kind or without an equal or an equivalent. There are many SharePoint search, retrieval, and discovery solutions in the market at this time. The president’s letter tells me:
‘Discover’ is able to understand what your users need, in terms of both information and ‘experts’ with whom they should be collaborating. This understanding is gained via our patent pending algorithms, which are able to examine user related content and ‘understand’ the subject matter being addressed, and therefore the subject matter that each and every one of your employees is focused on. Once this takes place, our products can deliver both info and people to your users, personalized to match their individual needs. The bottom line is that you need your experts, your most highly paid and critical personnel, to minimize the amount of time they spend doing administrative or manual activities and to maximize the time spent tackling the key problems that they are uniquely qualified to address. That is what DiscoverPoint does for you, and it pays for itself in very short order!
The company offers an Extensible Search Framework and an Advanced Connector Engine. The company also performs customer UIS (an acronym with which I am unfamiliar). The firm also has a software integration business, performs “high performance data indexing”, and offers professional services.
The company has an interesting marketing message. I noticed that Google’s result page includes a reference to IDOL, Autonomy’s system. We will monitor the firm’s trajectory because it looks like a hybrid which combines original software, a framework, consulting, and services. Maybe Forrester, Gartner, and Ovum will emulate Discover Technologies’ Swiss Army knife approach to findability and revenue generation?
Stephen E Arnold, February 16, 2012
Sponsored by Pandia.com
Exogenous Complexity 2: The Search Appliance
February 15, 2012
I noted a story about Fujitsu and its search appliance. What was interesting is that the product is being rolled out in Germany, a country where search and retrieval are often provided by European vendors. In fact, when I hear about Germany, I think about Exorbyte (structured data), Ontoprise (ontologies), SAP (for what it is worth, TREX and Inxight), and Lucene/Solr. I also know that Fabasoft Mindbreeze has some traction in Germany as does Microsoft with its Fast Search & Technology solution. Fast operated a translation and technical center in Germany for a while. Reaching farther into Europe, there are solutions in Norway, France, Italy, and Spain. Each of these countries’ enterprise search and retrieval vendors have customers in Germany. Even Oracle with its mixed search history with Germany’s major newspaper has customers. IBM is on the job as well, although I don’t know if Watson has made the nine hour flight from JFK to Frankfort yet. Google’s GSA or Google Search Appliance has made the trip, and, from what I understand, the results have been okay. Google itself commands more than 90 percent of the Web search traffic.
The key point. The search appliance is supposed to be simple. No complexity. An appliance. A search toaster which my dear, departed mother could operate.
The work is from Steinman Studios. A happy quack to http://steinmanstudios.com/german.html for the image which I finally tracked down.
In short, if your company operates in Germany, you have quite a few choices for a search and retrieval solution. The question becomes, “Why Fujitsu?” My response, “I don’t have a clue.”
Here’s the story which triggered my thoughts about exogenous complexity: “New Fujitsu Powered Enterprise Search Appliance Launched in Europe Through Stordis.” The news releases can disappear, so you may have to hunt around for this article and my link is dead.
Built on Fujitsu high performance hardware, the new appliance combines industry leading search software from Perfect Search Corporation with the Fujitsu NuVola Private Cloud Platform, to deliver security and ultimate scalability. Perfect Search’s patented software enables user to search up to a billion documents using a single appliance. The appliance uses unique disk based indexing rather than memory, requiring a fraction of the hardware and reducing overall solution costs, even when compared to open source alternatives solutions…Originally developed by Fujitsu Frontech North America, the PerfectSearch appliance is now being exclusively marketed throughout Europe by high performance technology distributor Stordis. PerfectSearch is the first of a series of new enterprise appliances based on the Fujitsu NuVola Private Cloud Platform that Stordis will be bringing to the European market during 2012.
No problem with the use of a US technology in a Japanese product sold in the German market via an intermediary with which I was not familiar. The Japanese are savvy managers, so this is a great idea.
What’s this play have to do with exogenous complexity?
Chiliad: Virtual Information Sharing
February 14, 2012
In 1999, Christine Maxwell, who created the “Magellan” search engine, Paul McOwen, co-founder of the National Center for Intelligent Information Retrieval for the National Science Foundation, and Howard Turtle, former chief scientist at West Publishing, formed Chiliad with the intention of creating a business-to-consumer shopping site with a natural language search engine.
And then September 11, 2001, happened. Chiliad turned its attention to the intelligence community. In 2007, with the FBI as its largest client, the company received $1.6 million in funding from a joint development project with various intelligence and military agencies to enhance Chiliad’s cross-agency knowledge fusion capability by tightly integrating cross-domain “trusted guard” capabilities to support distributed multi-level-security and by enhancing collaboration tools. For the past several years, every time someone at the FBI wanted to search for a name in its Investigative Data Warehouse, technology from Chiliad was working in the background.
Another outfit which connects dots. But Chiliad connects all the dots. Hmm. A categorical affirmative, and I don’t think this is possible.
Chiliad has solved two challenging problems. The first is the ability to rapidly search data collections at greater scale than any other offering in the market. The second is to allow search formulation and analysis in natural language. It offers Chiliad Discovery/Alert, a platform for search and knowledge discovery to operate in parallel across distributed repositories of unstructured and structured data; Peer-to-Peer Architecture, which allows organizations to distribute instances of the search, indexing, and analysis engine in a network of cooperating nodes in local or remote distributed networks; Distributed Search, which provides a search capability that works seamlessly in amounts of structured and unstructured data; Filtering and Alerting Service for tracking and receiving alerts about new data in real time; Discover Knowledge service, an integral component of the Discovery/Alert platform used for navigation and discovery; Discovery/Alert Geospatial Service, an organizing concept for information; and Global Knowledge Discovery technology. Rather than moving data across the network to a central indexing system, Chiliad’s technology allows organizations to put a Discovery/Alert node wherever information is managed. Each node is part of a secure peer-to-peer network that allows a query to be executed in parallel across all locations.
The company serves investigative analysis, information security, and research and development applications; and government and intelligence, insurance, law enforcement, and life sciences healthcare industries. Because Chiliad’s product is a platform, it faces competition in the enterprise market from large, better known vendors, such as Microsoft, IBM, Oracle, and SAP.
Stephen E Arnold, February 14, 2012
Sponsored by Pandia.com
Inforbix Cracks Next Generation Search for SolidWorks Users
February 13, 2012
Search means advertising to most Google users. In an enterprise—according to the LinkedIn discussions about enterprise search—the approach is anchored in the 1990s. The problem is that finding information requires a system which can handle content types that are of little interest to lawyers, accountants, and MBAs running a business today.
Without efficient access to such content as engineering drawings, specifications, quality control reports, and run-of-the-mill office information—costs go up. What’s worse is that more time is needed to locate a prior version of a component or locate the supplier who delivered on time and on budget work to the specification. So expensive professionals end up performing what I call Easter egg hunt research. The approach involves looking for colleagues, paging through lists of file names, and the “open, browse, close” approach to information retrieval.
Not surprisingly, the so called experts steer clear of pivotal information retrieval problems. Most search systems pick the ripe apples which are close to the ground. This means indexing Word documents, the versions of information in a content management system, or email.
I learned today that Inforbix, a company we have been tracking because it takes search to the next level, has rolled out two new products. These innovations are data apps which seamlessly aggregate product data from different file types, sources, and locations. The new Inforbix apps will help SolidWorks’ users get more out of their product data and become more productive while improving decision-making. Plus, Inforbix said that it would expand the data access to SolidWords EPDM, making it possible for SolidWords customers to get more from data managed by their PDM system.
The two products are Inforbix Charts and Inforbix Dashboard. Both complement Inforbix Tables which was released in October 2011.
Oleg Shilovitsky, founder of Inforbix, told me:
Manufacturing companies are drowning in the growing amount of product data generated and found within different file types, sources, and company data-silos. They are increasingly using a mix of vendor packages and solutions, all which generate, contain, manage, or store product data, creating a hodgepodge of resources to be combed through. Product data generated in a typical manufacturing company can be both unstructured (valuable BOM and assembly information spread out across different CAD drawings) and structured (CAD drawings within a PDM or PLM system). Our apps are tools that address specific product data tasks such as finding, re-using, and sharing product data. Inforbix can access product data within PDM systems such as ENOVIA SmarTeam and Autodesk Vault and make it available in meaningful ways to CAD and non-CAD users.
When I reviewed the system, I noted that Inforbix’s apps utilize product data semantic technology that automatically infer relationships between disparate sources of data. For example, Inforbix can semantically connect or link a SolidWorks CAD assembly found within EPDM with a related Excel file containing a BOM table stored on a file server in another department.
Inforbix Charts visualizes and presents data saved from Inforbix Tables. The product data is presented in charts that include information to help engineers better manage and run processes by identifying trends and patterns and improving data control. For example, Inforbix Charts visually presents the approval statuses of CAD and ECO documents by author, date approved, last modified date, etc.
Inforbix Dashboard dynamically collects and presents important statistics about engineering and manufacturing data and processes, such as how many versions of a particular CAD drawing currently exist, how many design revisions did it take to complete a CAD drawing, or the number of ECOs processed on time. Easy and intuitive to use, Inforbix Dashboard is an ideal tool for project managers.
SolidWords users can access Inforbix apps and their product data online. Current Inforbix customers can immediately begin using the Inforbix iPad app, available for free on the Apple App Store at http://www.inforbix.com/inforbix-mobile-search-for-cad-and-product-data-on-the-ipad/. Account access taps existing Inforbix credentials. New users are encouraged to register with Inforbix to enable the iPad app to access product data within their company. The apps soon will be available on Android devices.
A video preview of the iPad app is posted at http://www.inforbix.com/inforbix-ipad-app-first-preview/. For more information on Inforbix apps, visit http://www.inforbix.com.
Inforbix is a company on the move.
Stephen E Arnold, February 13, 2012
Sponsored by Pandia.com
NASA and Technical Information Search
February 2, 2012
I recall a Popular Science feature called “The Top 10 Failed NASA Missions.” I dug through my files and the story ran in March 2009. You can find a version of the article online, at least today, February 2, 2012, at 8 30 am Eastern. Tomorrow? Who knows.
A happy quack to The Doctor Weighs In.
Among the flops mentioned were:
- The Orbiting Carbon Observatory. I thought that the test lasted 17 minutes was interesting.
- Helios. This solar powered flying wing thing managed a 30 minute flight before crashing.
- Genesis. After catching “pieces of the sun” as Popular Science phrased it, the parachute did not open, but scientists were able to pick up pieces from the Utah desert. Progress!
- SBIRS. This was a passel of surveillance satellites. I don’t know much about SBIRS beyond the $10 billion cost overrun. According the Popular Science, one government official described SBIRS as a “useless ice cube.”
I was curious about post 2009 NASA activities. I could not locate a historical run down of alleged missteps, but I found “NASA Glory Mission Ends in Failure”, published by the BBC. The article asserted:
The Glory satellite lifted off from California on a quest to gather new data on factors that influence the climate. But about three minutes into the flight, telemetry indicated a problem. It appears the fairing – the part of the rocket which covers the satellite on top of the launcher – did not separate properly… Exactly the same problem befell NASA’s Orbiting Carbon Observatory (OCO) in 2009. It too launched on a Taurus XL rocket from the Vandenberg Air Force Base, and again the fairing failed to separate properly.
Wow. Exactly the same failure. The “Mishap Investigation Board” tackled the problem and apparently failed to fix the flop. I did a bit of poking around, and I learned that the NASA Safety Center analyzes system failures. In fact, there is a Web page called “System Failure Case Studies.” There are some interesting analyses, but I could not spot too many which focused on NASA’s own boo boos.
Curious about this apparent omission, I ran a query for NASA failure on www.usa.gov and www.science.gov. What did I learn? The top hit was from ASK magazine, a source which was new to me. The magazine’s “real” name is Ask the Academy, and it seems to be a Web site. What is interesting is that the top hit on USA.gov was “Success, Failure, and NASA Culture.” I read the article which was published originally in 2008. My hunch is that budget cuts are trimming the staff required to create original content. Recycling is a way to save some tax payer greenbacks I surmise. The 2008 write up republished on January 26, 2012 stated:
Improvement in system reliability came with increased bureaucracy, as systems engineering put a variety of crosschecks and reviews in place. System dependability improved, but these processes and technologies increased the cost of each vehicle. Eventually, and in response to pressures to decrease costs, engineers and managers cut back on safety and reliability measures.
The idea, I think, means that if something worked, then by eliminating the quality processes, the system which works is going to fail. I may not have that correct, but it seems that bureaucracy and efficiency help ensure failure. I never considered this management notion before, and frankly I am rejecting it.
In my experience, the processes which delivered success should be integrated into the work flow. Processes which do not contribute to success become the candidates for rationalization. In short, one engineers to deliver consistent success. One does not make decisions which deliver consistent failure.
The top hit on Science.gov was to “Failure Is Not an Option.” The hit was fascinating because it showed the Apollo 13 flight director in 1970. I did not recall this 1970 mission because I was indexing Latin sermons at some fourth rate university at the time. Wikipedia reminded me:
Apollo 13 was the seventh manned mission in the American Apollo space program and the third intended to land on the Moon. The craft was launched on April 11, 1970, at 13:13 CST. The lunar landing was aborted after an oxygen tank exploded two days later, crippling the service module upon which the Command Module depended. Despite great hardship caused by limited power, loss of cabin heat, shortage of potable water and the critical need to jury-rig the carbon dioxide removal system, the crew returned safely to Earth on April 17.
Okay, I suppose success means getting the crew back, which was a solid achievement in the midst of a mission failure.
So what?
Well, NASA is not exactly the government agency which resonates with consistent technology decisions. When it comes to search, much of the commercial scientific and technical search effort is a result of NASA’s need for an online index. That was in the 1970s, Apollo 13 time too.
Important developments in information access at NASA have been less frequent and, I would assert, few and far between. Today, NASA has a preference for Microsoft SharePoint, and we have learned has concluded its expensive procurement of an automated content indexing system. We are not sure which vendor is prepared to cope with exogenous complexity in the NASA environment.
We would assert that if NASA continues along its present course, successes will blended with some failures. One hopes that when it comes to search and retrieval, NASA makes informed decisions, not choices based on budget limitations, expediency, or overlooking exogenous factors such as complexity.
Stephen E Arnold, February 2, 2012
Sponsored by Pandia.com
Brainware Receives Rave Reviews
February 2, 2012
According to The Sacramento Bee article “Healthcare Payments Automation Summit (HPAS 2012) to Feature Brainware Customer Success Stories” Brainware Inc. is on display at the Healthcare Payments Automation Summit (HPAS 2012). Charles Kaplan, Vice President of Marketing for Brainware, brings attention to the excessive amount of unnecessary time that the healthcare industry spends pushing papers and states:
The success of providers like Mayo Clinic, Gundersen Lutheran and Resurrection offer resounding proof that intelligent data capture technology is the key to freeing those resources, turning slow, error-prone, manual data entry routines into efficient, transparent, well-oiled machines for generating profit and opportunity in healthcare.
However, Brainware’s technology could be considered backwoods to some. None of Brainware’s software platforms use taxonomies, indexing or any other type of tagging methods. This is in direct contrast to others such as Access Innovations who pride themselves in offering a full range of tagging features to produce more accurate results. Some might wonder if Brainware and trigrams really are a step in the right direction.
April Holmes, February 2, 2012
Sponsored by Pandia.com
Exogenous Complexity 1: Search
January 31, 2012
I am now using the phrase “exogenous complexity” to describe systems, methods, processes, and procedures which are likely to fail due to outside factors. This initial post focuses on indexing, but I will extend the concept to other content centric applications in the future. Disagree with me? Use the comments section of this blog, please.
What is an outside factor?
Let’s think about value adding indexing, content enrichment, or metatagging. The idea is that unstructured text contains entities, facts, bound phrases, and other identifiable entities. A key word search system is mostly blind to the meaning of a number in the form nnn nn nnnn, which in the United States is the pattern for a Social Security Number. There are similar patterns in Federal Express, financial, and other types of sequences. The idea is that a system will recognize these strings and tag them appropriately; for example:
nnn nn nnn Social Security Number
Thus, a query for Social Security Numbers will return a string of digits matching the pattern. The same logic can be applied to certain entities and with the help of a knowledge base, Bayesian numerical recipes, and other techniques such as synonym expansion determine that a query for Obama residence will return White House or a query for the White House will return links to the Obama residence.
One wishes that value added indexing systems were as predictable as a kabuki drama. What vendors of next generation content processing systems participate in is a kabuki which leads to failure two thirds of the time. A tragedy? It depends on whom one asks.
The problem is that companies offering automated solutions to value adding indexing, content enrichment, or metatagging are likely to fail for three reasons:
First, there is the issue of humans who use language in unexpected or what some poets call “fresh” or “metaphoric” methods. English is synthetic in that any string of sounds can be used in quite unexpected ways. Whether it is the use of the name of the fruit “mango” as a code name for software or whether it is the conversion of a noun like information into a verb like informationize which appears in Japanese government English language documents, the automated system may miss the boat. When the boat is missed, continued iterations try to arrive at the correct linkage, but anyone who has used fully automated systems know or who paid attention in math class, the recovery from an initial error can be time consuming and sometimes difficult. Therefore, an automated system—no matter how clever—may find itself fooled by the stream of content flowing through its content processing work flow. The user pays the price because false drops mean more work and suggestions which are not just off the mark, the suggestions are difficult for a human to figure out. You can get the inside dope on why poor suggestions are an issue in Thining, Fast and Slow.
Wordmap Introduces Taxonomy Connectors
January 30, 2012
According to the Wordmap.com article “Wordmap Taxonomy Connectors for SharePoint and Endeca” , users will be able to use its new Taxonomy Connectors directly with Endeca. Endeca Taxonomy Connector users will have the ability to use Wordmap to handle “all of their daily management tasks.”
A few notable benefits of the Taxonomy connector are,
No configuration needed for consuming systems. It can manage the taxonomy centrally and push out only relevant sections for indexing, navigation and search and taxonomy is seamlessly integrated into the content lifecycle.
The Wordmap Taxonomy platform definitely seems to be a viable tool when it comes to managing Endeca systems and seems like a no brainer for those using the platform. However, a few questions do come to mind. If Open Source connectors enter the scene will there still be a market for Wordmap connectors or what if Oracle decides to become a little stingier with its system access policies?
Users could still find that the Wordmap Taxonomy Connectors hit the spot or they could find the platform too cumbersome and go elsewhere. Guess it depends on “Which way the wind blows.”
We have heard of a push to make open source connectors available. With some firms charging as much as $20,000 for a connector, lower cost options or open source connectors could have a significant impact on the content processing sector.
April Holmes, Janaury 30, 2012
Sponsored by Pandia.com
Synaptica Independent Taxonomy Resource
January 27, 2012
Synaptica started out as Synapse Corporation under founders Trish Yancey and Dave Clarke. The company offered taxonomies, software solutions, and professional lexicography and indexing services for businesses and organizations based on its Synaptica product, a knowledge management and indexing software application, which enables enterprises in managing taxonomies, thesauri, classification schemes, authority control files, and indexes. In 2005, the company, renamed Synaptica, was acquired by Dow Jones and placed in its Factiva unit. Clarke has subsequently regained control of Synaptica.
The company has also has revamped its informational website, Taxonomy Warehouse – a free online resource that has answers enquiries about taxonomies. Named as one of KM World magazine’s “Trend-Setting Products of 2011,” Synaptica is an editorial tool designed for use by professional taxonomists. In 2011, the company added a complementary suite of front-end publication tools that make it easy for any taxonomy or ontology to be presented to end-users. The Ontology Publishing Suite gives administrators better control over which parts of a master ontology are exposed to end-users, as well as how they are laid out on-screen. Other parts of the Synaptica product suite include Synaptica Enterprise, the behind-the-firewall solution for larger organizations; Synaptica Express, a cloud-computing solution for individuals or small-business users; Synaptica IMS, a complementary suite of tools designed to support the human indexing of content using taxonomies stored in Synaptica; and Synaptica SharePoint Integration, an add-on module enabling taxonomies being managed within Synaptica to be applied as meta-tags to content being stored in SharePoint document libraries, as well as allowing for those same taxonomies to be used for search.
The technology has found a home in corporate, pharmaceutical, government, and e-commerce markets. Clients include Verizon, ProQuest, the BBC, and Harvard Business Publishing. Competitors LexisNexis, Dun & Bradstreet, and InsideView. (I would not include Concept Searching or Ontoprise in this short list due to exogenous complexity factors.)
Stephen E Arnold, January 27, 2012
Sponsored by Pandia.com
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