Social Networking Frederick Ghahramani co-founded AirG in 2000. Today the mobile social networking community has 20 million users. eMarketer spoke with him about what is driving growth and what it means for marketers.
eMarketer: What does this growth say about consumer attitudes to the mobile channel?
Frederick Ghahramani: It says that mobile-only social communities are an undisputed consumer phenomenon.
It is the mass market consumer that is driving the use of mobile content. When the right services are marketed correctly to a mass audience and can bring them together in one place on their mobile phone to chat, share photos and videos, search and check profiles, consumers will be engaged on their mobile phones?some for more than an hour each day.
eMarketer: How should marketers react to this growth? What should they do?
Mr. Ghahramani: With billions of advertising impressions generated per month there is a tremendous inventory available to marketers and advertisers to reach their target customers on their mobile phones.
eMarketer: What are user demographics like?
Mr. Ghahramani: The majority of customers spend more than an hour a day in the community. Nearly 60% don’t own a PC. Six in 10 have at least a high school education. The average annual income is $41,000, and the five most popular handsets used to access AirG all retail for less than $100 with a service contract.
The market is in a frenzy over new devices like the iPhone, but the reality is that the mass market consumer is using a handset that costs $100 or less to access mobile services.
eMarketer: How big do you think mobile social networking will get?
Mr. Ghahramani: According to Juniper Research, the number of users of mobile chat and dating services is expected to rise from just over 40 million in 2007 to 260 million in 2012, with revenues expected to exceed $1 billion in 2010.
ⓒ2007 eMarketer Inc.
Sunday, February 24, 2008
New W3C Standard for Opening up Data on the Semantic Web
W3C announced today the publication of SPARQL, the key standard for opening up data on the Semantic Web. With SPARQL query technology, pronounced "sparkle," people can focus on what they want to know rather than on the database technology or data format used behind the scenes to store the data. Because SPARQL queries express high-level goals, it is easier to extend them to unanticipated data sources, or even to port them to new applications.
Mashups with SPARQL
Many successful query languages exist, including standards such as SQL and XQuery. These were primarily designed for queries limited to a single product, format, type of information, or local data store. Traditionally, it has been necessary to formulate the same high-level query differently depending on application or the specific arrangement chosen for the relational database. And when querying multiple data sources it has been necessary to write logic to merge the results. These limitations have imposed higher developer costs and created barriers to incorporating new data sources.
The goal of the Semantic Web is to enable people to share, merge, and reuse data globally. SPARQL is designed for use at the scale of the Web, and thus enables queries over distributed data sources, independent of format. Creating a single query across diverse data stores is easier than having to create multiple queries; it also costs less and provides richer results.
Because SPARQL has no tie to a specific database format, it can be used to take advantage of the tidal wave of Web 2.0 data and mash it up with other Semantic Web resources. Furthermore, because disparate data sources may not have the same 'shape' or share the same properties, SPARQL is designed to query non-uniform data.
SPARQL Turns Data Access into a Web Service
The combination of the SPARQL query language and protocol creates a Web service in its purest sense; running on top of HTTP or SOAP, it provides a standard Web service for anything which asks a question.
"SPARQL's focus on querying the data models saves time for developers; there's no need for a host of little Web services to retrieve different aspects of the state of a system," explained Lee Feigenbaum, Chair of the RDF Data Access Working Group. "This allows the user of the SPARQL endpoint to ask any question -- it is as though they could design their own interface instead of having to work with a limited set of fixed services."
The SPARQL specification defines a query language and a protocol and works with the other core Semantic Web technologies from W3C: Resource Description Framework (RDF) for representing data; RDF Schema; Web Ontology Language (OWL) for building vocabularies; and Gleaning Resource Descriptions from Dialects of Languages (GRDDL), for automatically extracting Semantic Web data from documents. SPARQL also makes use of other W3C standards found in Web services implementations, such as Web Services Description Language (WSDL).
About W3CThe World Wide Web Consortium (W3C) is an international consortium where Member organizations, a full-time staff, and the public work together to develop Web standards. W3C primarily pursues its mission through the creation of Web standards and guidelines designed to ensure long-term growth for the Web. Over 400 organizations are Members of the Consortium. W3C is jointly run by the MIT Computer Science and Artificial Intelligence Laboratory (MIT CSAIL) in the USA, the European Research Consortium for Informatics and Mathematics (ERCIM) headquartered in France and Keio University in Japan,and has additional Offices worldwide. For more information see http://www.w3.org/
(W3C, Jan., 15th 2008, Original press release)
Mashups with SPARQL
Many successful query languages exist, including standards such as SQL and XQuery. These were primarily designed for queries limited to a single product, format, type of information, or local data store. Traditionally, it has been necessary to formulate the same high-level query differently depending on application or the specific arrangement chosen for the relational database. And when querying multiple data sources it has been necessary to write logic to merge the results. These limitations have imposed higher developer costs and created barriers to incorporating new data sources.
The goal of the Semantic Web is to enable people to share, merge, and reuse data globally. SPARQL is designed for use at the scale of the Web, and thus enables queries over distributed data sources, independent of format. Creating a single query across diverse data stores is easier than having to create multiple queries; it also costs less and provides richer results.
Because SPARQL has no tie to a specific database format, it can be used to take advantage of the tidal wave of Web 2.0 data and mash it up with other Semantic Web resources. Furthermore, because disparate data sources may not have the same 'shape' or share the same properties, SPARQL is designed to query non-uniform data.
SPARQL Turns Data Access into a Web Service
The combination of the SPARQL query language and protocol creates a Web service in its purest sense; running on top of HTTP or SOAP, it provides a standard Web service for anything which asks a question.
"SPARQL's focus on querying the data models saves time for developers; there's no need for a host of little Web services to retrieve different aspects of the state of a system," explained Lee Feigenbaum, Chair of the RDF Data Access Working Group. "This allows the user of the SPARQL endpoint to ask any question -- it is as though they could design their own interface instead of having to work with a limited set of fixed services."
The SPARQL specification defines a query language and a protocol and works with the other core Semantic Web technologies from W3C: Resource Description Framework (RDF) for representing data; RDF Schema; Web Ontology Language (OWL) for building vocabularies; and Gleaning Resource Descriptions from Dialects of Languages (GRDDL), for automatically extracting Semantic Web data from documents. SPARQL also makes use of other W3C standards found in Web services implementations, such as Web Services Description Language (WSDL).
About W3CThe World Wide Web Consortium (W3C) is an international consortium where Member organizations, a full-time staff, and the public work together to develop Web standards. W3C primarily pursues its mission through the creation of Web standards and guidelines designed to ensure long-term growth for the Web. Over 400 organizations are Members of the Consortium. W3C is jointly run by the MIT Computer Science and Artificial Intelligence Laboratory (MIT CSAIL) in the USA, the European Research Consortium for Informatics and Mathematics (ERCIM) headquartered in France and Keio University in Japan,and has additional Offices worldwide. For more information see http://www.w3.org/
(W3C, Jan., 15th 2008, Original press release)
Thursday, February 21, 2008
Enterprise Search: Trends for 2008
by Adriaan Bloem
Overall, the search marketplace continues to surprise, sometimes delight, and often obfuscate prospective customers. Nevertheless, some key trends are emerging.
Refining the Experience
After nearly a decade of commentators criticizing the usability of enterprise search tools, within the past few years, vendors have begun to take note. I can't say that all innovation here constitutes improvement, but on the whole, we see a trend towards greater adoption of consumer search experiences.
Navigating Search
Search vendor Endeca may have applied for patents on "guided navigation," but the reality is that nearly every vendor can provide some degree of results categorization, be it clustering, browsable categories, or any other approach. The hype-du-jour is clicking a query together from the navigation built -- browsing the search results. Of course, distilling the terms for navigation is relatively easy when the source is structured content or when metadata can provide guidance. But it gets very much more difficult where unstructured data is in the mix: here vendors frequently differentiate according to their auto-extraction facilities that can glean facets and terms from your corpus without you having to tag documents. Your mileage will vary.
Analyzing Search
What is management without measurement? Seems obvious, but most search tools -- until recently -- had no built-in capacity to analyze the rich information found in their logs. Even today, there is wide variances among the tools.
Using analytics to improve search is a no-brainer. You can find out what people are actually looking for, what they are finding, what they are not finding, and how often. It's no replacement for focus groups and real user testing, but it's a fine complement. Unfortunately, even those systems with nice query-and-reporting interfaces often don't link directly to the administrative panels (e.g., for hit boosting or best bets) to redress the problems you find, but arming yourself with good metrics is a very useful start.
Uncrowding Search
Enterprise search vendors are consciously making their default search results look like Google's, even down to the green titles and blue hyperlinks. Why? Evidence suggests that searchers have more confidence in Googlesque results pages. Nevertheless, enterprise search is often more complicated than public web search; sometimes enterprise employees need more bells and whistles, including folders and categories and other data on the results page. That's one of the reasons why we take a scenario-based analysis to evaluating search technologies, and you should too.
Marketplace Ferment
The search marketplace continues to evolve in a herky-jerk fashion, with acquisitions (e.g., Convera to FAST and VisualSciences to Omniture) and bankruptcies (e.g., Mondosoft, Speed-of-Mind). Out of this ferment, some clear trends are emerging.
Escape from MOSS
Several enterprise search vendors did a great business by selling alternatives to the quite deficient search services within the first two versions of SharePoint. But now that Redmond has addressed SharePoint search aggressively -- at least on paper -- those companies are rapidly re-tooling to serve other customers. At least one of them, Mondosoft, did not execute well on the transition, and was purchased by a smaller competitor out of bankruptcy.
The irony is that MOSS Search is not a slam dunk. There is room for alternatives, even in Microsoft-oriented enterprises.
Decline of SaaS Search
Software-as-a-Service delivery models are hot all across the software landscape....with the exception of search. Early hosted player Blossom has faded to near obscurity. Hosted CMS vendor CrownPeak has pulled back from its (originally ambitious) plans for an advanced SaaS search offering. The grand-daddy of hosted search, Atomz, was acquired by e-commerce metrics company WebSideStory in 2005, who merged with niche analytics vendor VisualSciences, took that name, tried to sell off its assets, and was ultimately acquired by mainstream web analytics vendor Omniture. As of Q4, 2007, the future for VisualSciences' search customers remains quite unsettled. To be sure, some enterprise search vendors offer their "normal" product in a hosted environment, often in conjunction with a consulting or datacenter partner. However, these are not true, built-from-the-ground-up, multi-tenant SaaS offerings. They are managed services offerings using traditional, installed software.
There are a couple reasons for the demise of SaaS search. First, from day one it was really limited primarily to the website search scenario -- an important use case to be sure -- but not as lucrative or as high-value as multi-repository enterprise search, which depends heavily on the kind of WAN connectivity and in situ software connectors that SaaS vendors simply cannot provide today. Second, and perhaps more importantly: the dramatic rise of search appliance vendors (especially Google) has surely cut into demand for simple, web-oriented solutions of the type offered by SaaS vendors (Google itself put its basic hosted solution on hold for a few years while it waited for the Appliance to gather momentum). This doesn't mean you should avoid going the SaaS route; just sign on with your eyes open and make sure you understand the provider's future plans and focus.
Talking Search/BI Convergence
In the past year, the marketplace has seen substantial discussion and speculation about the "convergence" of big-time structured search (usually under the auspices of Business Intelligence tools) and big-time unstructured search (usually by traditional enterprise search products).
Enthusiasm was fueled when BI vendor Business Objects acquired text mining supplier, Inxight (Business Objects itself was subsequently acquired by SAP). To us, the convergence remains mostly talk. Most enterprise search tools that could retrieve information from unstructured datasets could also access and index databases as well. However, vice-versa was not always true: BI vendors -- and their customers -- don't always understand unstructured content.
Clearly, there are use-cases for this sort of convergence. For example, companies want to mine customer comments as well as customer data. But today, the two software segments remain quite distinct, mostly because customers are still trying to solve basic search and BI problems, before moving on to more advanced challenges.
Google Continues Long March to the Enterprise
This report contains a section focused on the Google Appliance, the Trojan horse of the enterprise search world. Google continues to improve its appliance -- and intimidate its competition -- even though (as you will see in our chapter), the appliance remains somewhat deficient as an enterprise search tool. Google's long-term plans for the appliance surpass simple search. Google can use it as a platform for other enterprise applications, perhaps some offered on a hosted basis. But it's a long way from the public web to the enterprise, and customers report that once you reach the limits of the appliance, you're pretty much stuck. It's a service in a box. Google found a great, underserved niche for simple search and has executed well on it. But it remains unclear whether Google the company truly understands the workaday needs of the enterprise.
Enduring Technical Challenges
One of the great surprises -- and, for many customers, disappointments -- of enterprise search is how technically challenging it becomes after you get beyond the basics. And you can get beyond the basics pretty quickly. Search and the discipline of information retrieval are among the most complex computer endeavors we face today. The nature of language itself is inherently baffling. Humans cannot make sense of some documents. Software doesn't do much better. But if technical challenges endure, then at least two trends in particular stand out today.
Platforms and Products Diverge
Is the fundamental problem with enterprise search a lack of power or a surfeit of complexity? The marketplace doesn't seem to be able to decide. Some vendors, such as IBM, continue to expand on their multifaceted search toolkits. Meanwhile, competitor Oracle is working to simplify its offering and conceal or abstract much of the underlying power. Neither approach is universally ideal, but it is a measure of a maturing market that vendors are tending to go one direction or the other. The good news for you the buyer is that you have clear choices: fulfill an immediate business need or develop long-term capacity. That debate is as old as enterprises have been adopting software. We make no judgments, but point out in our report that you have solid alternatives either way.
Application Management Conundrum
If search is a software application, then it should be managed like one. This sometimes comes as a surprise to even the most seasoned enterprise IT team who may labor under the misimpression that even a lower-end search product is "install and forget." Even the lowest-end search platforms -- and even appliances like Google -- can be configured and extended.
But, of course, configurations beg management and testing themselves. In short, enterprise search has the enduring need for proper software development lifecycles and code / configuration management.
Unfortunately, most (if not all) search platforms do not make configuration management simple. Most assume you will not have a development, staging, or QA instance of the search application itself. Many allow for overlapping code, command-line, and browser-based configurations and customizations, making it hard for administrators and developers to separate concerns.
As search tools get ever more powerful, the more it becomes incumbent on you to manage them with the same care that you manage your other complex, mission-critical applications.
*Wrapping Up
So, looking at the problem of enterprise search, you'll continue to see new buzzwords, but mostly you will continue to face the enduring challenge of collecting, securing, understanding, and displaying content. Search technology does get incrementally better, but your repositories are getting monumentally larger. Treat search like the serious project it is before you invest in any tool.
Source: http://www.cmswatch.com/Feature/170-Search-Trends
Overall, the search marketplace continues to surprise, sometimes delight, and often obfuscate prospective customers. Nevertheless, some key trends are emerging.
Refining the Experience
After nearly a decade of commentators criticizing the usability of enterprise search tools, within the past few years, vendors have begun to take note. I can't say that all innovation here constitutes improvement, but on the whole, we see a trend towards greater adoption of consumer search experiences.
Navigating Search
Search vendor Endeca may have applied for patents on "guided navigation," but the reality is that nearly every vendor can provide some degree of results categorization, be it clustering, browsable categories, or any other approach. The hype-du-jour is clicking a query together from the navigation built -- browsing the search results. Of course, distilling the terms for navigation is relatively easy when the source is structured content or when metadata can provide guidance. But it gets very much more difficult where unstructured data is in the mix: here vendors frequently differentiate according to their auto-extraction facilities that can glean facets and terms from your corpus without you having to tag documents. Your mileage will vary.
Analyzing Search
What is management without measurement? Seems obvious, but most search tools -- until recently -- had no built-in capacity to analyze the rich information found in their logs. Even today, there is wide variances among the tools.
Using analytics to improve search is a no-brainer. You can find out what people are actually looking for, what they are finding, what they are not finding, and how often. It's no replacement for focus groups and real user testing, but it's a fine complement. Unfortunately, even those systems with nice query-and-reporting interfaces often don't link directly to the administrative panels (e.g., for hit boosting or best bets) to redress the problems you find, but arming yourself with good metrics is a very useful start.
Uncrowding Search
Enterprise search vendors are consciously making their default search results look like Google's, even down to the green titles and blue hyperlinks. Why? Evidence suggests that searchers have more confidence in Googlesque results pages. Nevertheless, enterprise search is often more complicated than public web search; sometimes enterprise employees need more bells and whistles, including folders and categories and other data on the results page. That's one of the reasons why we take a scenario-based analysis to evaluating search technologies, and you should too.
Marketplace Ferment
The search marketplace continues to evolve in a herky-jerk fashion, with acquisitions (e.g., Convera to FAST and VisualSciences to Omniture) and bankruptcies (e.g., Mondosoft, Speed-of-Mind). Out of this ferment, some clear trends are emerging.
Escape from MOSS
Several enterprise search vendors did a great business by selling alternatives to the quite deficient search services within the first two versions of SharePoint. But now that Redmond has addressed SharePoint search aggressively -- at least on paper -- those companies are rapidly re-tooling to serve other customers. At least one of them, Mondosoft, did not execute well on the transition, and was purchased by a smaller competitor out of bankruptcy.
The irony is that MOSS Search is not a slam dunk. There is room for alternatives, even in Microsoft-oriented enterprises.
Decline of SaaS Search
Software-as-a-Service delivery models are hot all across the software landscape....with the exception of search. Early hosted player Blossom has faded to near obscurity. Hosted CMS vendor CrownPeak has pulled back from its (originally ambitious) plans for an advanced SaaS search offering. The grand-daddy of hosted search, Atomz, was acquired by e-commerce metrics company WebSideStory in 2005, who merged with niche analytics vendor VisualSciences, took that name, tried to sell off its assets, and was ultimately acquired by mainstream web analytics vendor Omniture. As of Q4, 2007, the future for VisualSciences' search customers remains quite unsettled. To be sure, some enterprise search vendors offer their "normal" product in a hosted environment, often in conjunction with a consulting or datacenter partner. However, these are not true, built-from-the-ground-up, multi-tenant SaaS offerings. They are managed services offerings using traditional, installed software.
There are a couple reasons for the demise of SaaS search. First, from day one it was really limited primarily to the website search scenario -- an important use case to be sure -- but not as lucrative or as high-value as multi-repository enterprise search, which depends heavily on the kind of WAN connectivity and in situ software connectors that SaaS vendors simply cannot provide today. Second, and perhaps more importantly: the dramatic rise of search appliance vendors (especially Google) has surely cut into demand for simple, web-oriented solutions of the type offered by SaaS vendors (Google itself put its basic hosted solution on hold for a few years while it waited for the Appliance to gather momentum). This doesn't mean you should avoid going the SaaS route; just sign on with your eyes open and make sure you understand the provider's future plans and focus.
Talking Search/BI Convergence
In the past year, the marketplace has seen substantial discussion and speculation about the "convergence" of big-time structured search (usually under the auspices of Business Intelligence tools) and big-time unstructured search (usually by traditional enterprise search products).
Enthusiasm was fueled when BI vendor Business Objects acquired text mining supplier, Inxight (Business Objects itself was subsequently acquired by SAP). To us, the convergence remains mostly talk. Most enterprise search tools that could retrieve information from unstructured datasets could also access and index databases as well. However, vice-versa was not always true: BI vendors -- and their customers -- don't always understand unstructured content.
Clearly, there are use-cases for this sort of convergence. For example, companies want to mine customer comments as well as customer data. But today, the two software segments remain quite distinct, mostly because customers are still trying to solve basic search and BI problems, before moving on to more advanced challenges.
Google Continues Long March to the Enterprise
This report contains a section focused on the Google Appliance, the Trojan horse of the enterprise search world. Google continues to improve its appliance -- and intimidate its competition -- even though (as you will see in our chapter), the appliance remains somewhat deficient as an enterprise search tool. Google's long-term plans for the appliance surpass simple search. Google can use it as a platform for other enterprise applications, perhaps some offered on a hosted basis. But it's a long way from the public web to the enterprise, and customers report that once you reach the limits of the appliance, you're pretty much stuck. It's a service in a box. Google found a great, underserved niche for simple search and has executed well on it. But it remains unclear whether Google the company truly understands the workaday needs of the enterprise.
Enduring Technical Challenges
One of the great surprises -- and, for many customers, disappointments -- of enterprise search is how technically challenging it becomes after you get beyond the basics. And you can get beyond the basics pretty quickly. Search and the discipline of information retrieval are among the most complex computer endeavors we face today. The nature of language itself is inherently baffling. Humans cannot make sense of some documents. Software doesn't do much better. But if technical challenges endure, then at least two trends in particular stand out today.
Platforms and Products Diverge
Is the fundamental problem with enterprise search a lack of power or a surfeit of complexity? The marketplace doesn't seem to be able to decide. Some vendors, such as IBM, continue to expand on their multifaceted search toolkits. Meanwhile, competitor Oracle is working to simplify its offering and conceal or abstract much of the underlying power. Neither approach is universally ideal, but it is a measure of a maturing market that vendors are tending to go one direction or the other. The good news for you the buyer is that you have clear choices: fulfill an immediate business need or develop long-term capacity. That debate is as old as enterprises have been adopting software. We make no judgments, but point out in our report that you have solid alternatives either way.
Application Management Conundrum
If search is a software application, then it should be managed like one. This sometimes comes as a surprise to even the most seasoned enterprise IT team who may labor under the misimpression that even a lower-end search product is "install and forget." Even the lowest-end search platforms -- and even appliances like Google -- can be configured and extended.
But, of course, configurations beg management and testing themselves. In short, enterprise search has the enduring need for proper software development lifecycles and code / configuration management.
Unfortunately, most (if not all) search platforms do not make configuration management simple. Most assume you will not have a development, staging, or QA instance of the search application itself. Many allow for overlapping code, command-line, and browser-based configurations and customizations, making it hard for administrators and developers to separate concerns.
As search tools get ever more powerful, the more it becomes incumbent on you to manage them with the same care that you manage your other complex, mission-critical applications.
*Wrapping Up
So, looking at the problem of enterprise search, you'll continue to see new buzzwords, but mostly you will continue to face the enduring challenge of collecting, securing, understanding, and displaying content. Search technology does get incrementally better, but your repositories are getting monumentally larger. Treat search like the serious project it is before you invest in any tool.
Source: http://www.cmswatch.com/Feature/170-Search-Trends
Monday, February 11, 2008
From-the-Top Interview with ontoprise GmbH
Written by Scott Koegler
This From-the-Top interview is with Prof. Dr. Angele Jürgen, Co-founder and CTO of Ontoprise GmbH.
SR: What is the current focus of your company's business?
Jürgen: The focus of our business is to provide mature and industry-proven Semantic Web infrastructure technologies like reasoners, ontology modeling environments, etc. to our partners and clients. Our partners create complete semantic solutions or enhance their own existing products with these technologies or directly apply our products within their customer projects. In this way, we are aiming to expand our excellent positioning as a technology and market leader.
SR: How has this focus changed in the last 2 years?
Jürgen: Having successfully implemented several projects in the industry ourselves, we noticed that an increased growth can only be achieved with a strong partner base. Thus, doing business with and via our partners became the focal point of our ambitions. We are very proud that we successfully have set up several solid and working partnerships already.
SR: What are your current initiatives?
Jürgen: From a technical point of view the “marriage” of the two different logical frameworks OWL and F-logic /Rules is the key development initiative we are undertaking, combining the advantages of both approaches. Beside that, we just started a service initiative around Semantic MediaWiki. The combination of our quality-approved distribution of Semantic MediaWiki, a set of powerful extensions for the productive use of SMW, and our high-level services is the perfect starting point for companies to introduce and operate Semantic MediaWiki in their organizations.
SR: How has the market for semantic technology changed over the last year?
Jürgen: Up to now, early adopters apply our products in productive environments. In the last year, semantic technology became more and more aware in the industry. For instance, the rate of participants from the industry at the Semtech conference in San Jose has grown strongly and there was a great atmosphere of departure. So you got the feeling that corporate Semantic Web really starts to take off, which is backed by the growing number of customers for ontoprise. What are the greatest challenges to adopting and implementing semantic technology for your customers? The challenge is to bring a new, innovative and complex technology into the mindset of the customers. Similar to database technology 30 years ago, it is a complex technology and customers have to understand the huge possibilities you gain with that technology. Furthermore, it is always important to give the customer a realistic picture of benefit from semantics.
SR: How are you helping your customers address these challenges?
Jürgen: Basically, by delivering mature and complete products focusing on real-life business needs and by showing our customers industrial references which have proven that the value is greater than the challenges. What do you believe to be the greatest contribution semantic technology will make? Semantic technologies allow us to unleash logics from applications and to bring it to a more abstract and flexible layer. This allows complex things to be described more easily and in an understandable way not only for the IT experts, and that increases the flexibility.
SR: Describe your company's position in the industry with regard to the solutions you deliver.
Jürgen: Looking at our history, our experiences and our customers, we can truly claim to provide mature and industry-proven Semantic Web infrastructure technologies. By that, we are delivering the core backbone to the SemanticWeb, setting standards together with our partners and clients. For example, we are the only company worldwide with a reasoner for both logical frameworks: OWL and F-logic/Rules.
SR: What do you believe to be the state of the industry in terms of growth, maturity, and availability of viable products to address the needs of implementers of semantic technology?
Jürgen: The market is on one hand still in an innovative state – compared to the huge possibilities of semantic technologies in general. One the other hand, we have several customers using ontologies successfully to improve their processes. Kuka Robot, one of the world’s largest suppliers of industrial robots, has just rolled-out the second generation of Kuka.Expert to their service technicians worldwide after the productive use of the first implementation for approximately 3 years.
--------------------------------------------------------------------------------
Prof. Dr. Angele Jürgen is Co-founder and CTO of Ontoprise GmbH, a provider of semantic technologies. In 1994, he became a full professor in applied computer science at the University of Applied Sciences, Braunschweig, Gemany. From 1989 to 1994, he was a research and teaching assistant at the University of Karlsruhe, Institute AIFB. He did research on the execution of the knowledge acquisition and representation language KARL, which led to a Ph.D. (Dr. rer. pol.) from the University of Karlsruhe in 1993. From 1985 to 1989, he worked for the companies AEG, Konstanz, Germany, and SEMA GROUP, Ulm, Germany. He received the diploma degree in computer science in 1985 from the University of Karlsruhe. He published around 90 papers as books and journals, and as book, conference, and workshop contributions. Topics were about Semantic Web, semantic technologies, knowledge representation, and their practical applications. He is leading several research and commercial projects. He gave more than 55 courses at Berufsakademien, Fachhochschulen and Universities. Topics were about: Expert Systems, Software Engineering, World Wide Web, Database Systems, Digital Image Analysis, Computer Graphics, Mathematics. He supervised around 30 master theses and PhDs.
Source: www.semanticreport.com
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