OntologySummit2011: Strategies for "Making the Case" community input    (2LKY)

Our Audience:    (2OWD)

We need a (slightly) different message for each of the different audiences. These are categories of people we need to 'Make our Case' to:    (2OWE)

What are the different (customized) message we need for each of the above folks? ... Identify the category and help craft a compelling message to that audience.    (2OWL)

"Sound Bites" and "Elevator Pitches"    (2NFS)

Let's share some good "Sound Bites" or "Elevator Pitches" that will help make the case for ontology - enter you input here - http://ontolog.cim3.net/file/work/OntologySummit2011/Survey/Survey01_Soundbite-Pitch/survey01.html ... Input Form    (2LY6)

Collected "Sound Bites"    (2LX0)

These are short blurbs that can grab people's attention to make a point. A sound bite is a very short piece of a speech taken from a longer speech or an interview in which someone with authority or the average "man on the street" says something which is considered by those who edit the speech or interview to be the most important point.    (2LX1)

Collected "Elevator Pitches"    (2LX6)

something you can say summarily to try to convince others to buy your idea. An elevator pitch or elevator speech is an overview of a product, service, person, group or organization, or project and is often a part of a fundraising, marketing communications, brand, or public relations program. The name "elevator pitch" reflects the idea that it should be possible to deliver an elevator pitch in the time span of an elevator ride, or approximately thirty seconds to two minutes.    (2LX7)

... (entry) ...    (2LXD)

Information comes in many forms; evolving and expanding too. Translating between these different representations is difficult and expensive, and absorbs an increasing level of computing and human resources. Ontology and semantic technology offer the only viable approach to mastering this growing babel of alternative notations, conventions and languages. Combining AI-developed reasoning methods with industrial-scale data handling techniques, and based on rigorous logical foundations, they have the expressive semantic reach to approach that of human thought, while being founded on proven computational methods which can effectively handle immense amounts of data. The ability to rapidly integrate information between people, agencies and machines is essential for large-scale IT systems used by humans tasked with time-critical decision-making, who need information presented in human-oriented ways, yet backed up by rigorous machine reasoning.    (2LX9)

Ontology and semantic technology impacts the foundations on how we compute, how we can tackle trust and confidence issues, and how we improve our citizenry's cyber-capability. Semantic breadth and precision is essential to human-computer interaction, intelligent user interface design and natural language processing. Semantic precision enables the development of systems with predictable performance. Semantics drive intelligent tutoring systems, provide clarity on educational content, and enable professional communities to clarify domain knowledge explicitly.    (2LXA)

Commercial success is also vitally dependent upon mastery of information. In many business models, information itself has become the most important capital resource. Ontology is the science of information in this sense: its semantic theories provide a unified account of how human thought and machine data can be united into a Web of meaning.    (2LXB)

Ontology supports consistent data definitions across the enterprise and thus data sharing. It does so in a principled way that allows for validation of data and reasoning with data, combining data from across the enterprise to arrive at novel conclusions. A large enterprise-wide database of validated and consistent data also extends the reach of statistical methods for data mining.    (2M58)

To a computer, a normal web page is just a collection of meaningless symbols (text). It has no idea how to extract meaning from it. What computerized systems, such as business systems, need is information structured in such a way that it can be reasoned with and where definitions of terms are clear and unambiguous. Computers, after all, are very pedantic, and very stupid, compared to people. That's what formal knowledge representation can do for us, and an ontology is just such an artifact.    (2M56)

James, it's tough to make a business case for infrastructure. But we should look at what's happening with business semantic and ontological technologies. These maturing technologies are about defining the language of work at the core of our business - the deep genetics of our business and what we do for a living. An ontology is an explicit, transparent model of work - and powerful ontology-enhanced systems can be put to work day-in day-out by both people and machines working together - for huge productivity advances and even better, such systems can open the door to business model evolution - not like our ERP systems! And you know, genetics is all about survival. If ontological technology can help us play to our strengths, by making what we are good at explicit and more useable, I think we should look at a project.    (2M5A)

James, as you know from your board meetings, it's tough to make a business case for infrastructure. That's the challenge for computing - even though it's the ante to play, it's always painful to have to invest.    (2M5C)

But it might not be so painful with the new business semantic and ontological technologies. These technologies are game changers. Everything in IT up till now has been about technology first and business a distant second. But semantic and ontological technology are different - they are explicitly, fluidly and directly about the core of our business - which is the work of our business. No other technology has ever really been primarily about the work of business. For the first time we can set our business analysts on projects where 100% of the time they are wrestling with how to do business better - using business terms that machines can also make use of - and the results enable machines and people to work together in amazing new ways. Whether it's supply chain or configuration management or financial services control or building optimization or customer services, the new semantic and ontological technologies are about defining and modeling the genetics of business, if you will. And as we know from evolution, genetics is all about survival! So mastering the genetics of our business - which is what semantic and ontological technology is all about - will become both a matter of survival, and an opportunity to come out on top.    (2M5D)

So, we can start with a little project and just grow from there. Typically with semantic and ontological technology, boiling the ocean is not on! Such projects should be incremental and adaptive and about successful evolution. It's almost like teaching machines the language of business! Up until now, the gap between machines and people has been enormous - requiring our dedicated and expensive cadre of IT specialists. The new technologies coming out now however makes it possible to bridge the gap between machines and people. So the enormous power of today's computers can be delivered right to the core of our business. The transition won't be easy - and there will be winners and losers. But we'll never be able to go back. And the winners will be those that stepped up with semantic and ontological technology, stepped up to unleash the power of business language tied to power of computing machines. We'll earn an advantage that we'll own forever. Because defining the real semantics of the work we do is defining and even improving our business genetic identity. Semantic and ontological technology is the tool kit and the insurance policy that our business model will persist and thrive.    (2M5E)

I know you've had some ideas about how you'd like the organization to evolve. Let's look at how a little project could be a test of the promise of semantic and ontological technology -- and a step forward in the direction of your vision.    (2M5F)

Every human has a different perspective on the world. When they express those perspectives, they use models of the world that they carry in their heads, and language derived from their individual life experiences. If you are trying to tame the complexity caused by these perspectives, you have two choices: (1) try to alter the way people express themselves to align with an external model - which is virtually impossible - or (2) allow people to express themselves in local terms, then reconcile those terms with all others, to discover similarities and differences. This heightened awareness will help you make better decisions. This works for conversations between people as well as between computer systems. Ontologies, and the software behind them, help you to do this.    (2MEH)

"Using information technology necessarily requires coding and digitising your real business world and every professional aims to do this as accurately as possible.    (2NG5)

Nonetheless, with poor preparation and modelling, valuable and necessary meaning can be irretrievably lost. What remains will be a reflection of the measure of control that you maintain over your world of meanings, important to you and your business.    (2NG6)

Ontology takes this whole process to a new level with improved chances of capturing greater detail and accuracy of your business and how it works and thus deliver greater value for your IT investment. However, as with all modelling processes, whoever controls the design of your information systems has control over how your business is 'understood' by those systems.    (2NG7)

Good ontologists working with you will have the intellectual modesty to accept that they can't model your business for you but can offer valuable, time and cost saving methods that will help you gain more from your technology."    (2NG8)

"Ontology-based processes and systems increase market standing, productivity, innovation and liquidity. Further, participative ontology development fosters interorganizational trust. Dramatic payback in a matter of months is typical. As contrasted to the typical montage of policies, procedures, rules, taxonomies, product nomenclatures, data base schemas, etc., ontology-based business practices and systems achieve new levels of coherency, efficiency, and agility. A participative ontology development project is a powerful way to align IT and all other departments with business strategy. Ontology development is low risk. One can start small, measure the benefits, evolve the organization and expand to the next level. Ontology maintenance becomes a part of everyone’s regular job. As Quality Guru Phil Crosby has said, "As the business grows it becomes harder for management to know what is happening and practically impossible to know what is NOT happening." Leaders of ontology-based enterprises don’t have that problem."    (2OXG)

see this post too!    (2OXH)

Our ability to share, manage, analyze, communicate and act upon information is at the foundation of the modern enterprise. Information sharing is essential for enterprise supply chains, fighting terrorism and integrating enterprise applications. Yet, this essential capability has remained difficult in information systems which are frequently isolated, stove piped and difficult to integrate. The inability of our systems to share information hampers the ability of our organizations to collaborate - for our processes, services and information resources to work together. Some estimate that more than 1/3 of our information technology budgets are consumed overcoming this "semantic friction" in our systems and that the costs to society from our failure to share and collaborate is many times the systems overhead.    (2RXA)

Mainstream tools for information and data modeling are effective at defining a particular data model for a particular application in a particular technology to solve a particular problem. But they suffer when applied to multiple applications for multiple purposes over multiple technologies to deal with unanticipated needs and opportunities. Most mainstream modeling techniques are challenged when faced with federating independently conceived models.    (2RXB)

Semantic technologies can serve to define and connect the meaning of data, processes and services as ontologies. Contrast this ontology approach with just static data structures identified with tags names as are the foundation of classical data modeling and data schema. Ontologies offer the potential for making a substantial contribution to solving the "data problem" though better understanding of the meaning behind the symbols we use in our data and data schema. By better understanding we are able to achieve improved data sharing and federation. This is not just theory, there are multiple proof points where ontologies are providing real solutions today, yet there is still substantial opportunity to develop and leverage these technologies further.    (2RXC)

Every {unit in your organization} that processes information or has decision making capable carries with it assumptions about how the world works. Ontology makes these assumptions explicit and accessible, helping you strike that critical balance between achieving short term goals while planning for the long game - granting a decisive strategic advantage to your organization.    (2S34)

A vital problem facing every growing, changing organization is developing solutions that can adapt to new and dynamic environments, employees, technologies and market realities. In any organization, each and every unit that collects or processes information or makes decisions, employs certain assumptions about how their (part) of the world works - or is important enough to know about.    (2S36)

Ontology based solutions makes these assumptions explicit and accessible across the organization. Ontological analysis and tools facilitate a streamlined integration of new market forces, new systems, new people - in effect any new assumptions. They provide a powerful framework to manage, update and evolve the high value components of responsive, agile organizations.    (2S37)

While the particular technology implementation for your organization depends on {your current commitments and available resources}; ontological analysis is critical in allowing you to plan for the long term while addressing current needs. It does so by identifying what parts of an organizations assumptions can provide a real benefit to the operation and delivery of (service / product / other) for ___, within an extensible, modular framework. With this understanding, you can effectively pick the right technology implementation to strike that balance between long and short term objectives.    (2S38)

... (next entry) ...    (2M6K)

Let's share some the Pros and Cons ... Arguments for Ontology, Arguments Against Ontology as well as effective Counter-arguments below. (ref.)    (2NFM)

(A) Arguments For Ontology    (2NFN)

Arguments you have been able to use successfully to promote ontologies ...    (2NFO)

(B) Arguments Against Ontology    (2NFT)

Arguments you have had to counter and found difficult to overcome ...}    (2NFU)

(C) Common Arguments against Ontology and their Counter-arguments    (2NFY)

Arguments commonly used against Ontology, which you have been able to effectively provide counter-argument(s) for (we need both sides ... and presumably, this category would include (derogatory) myths about Ontology and how they could be debunked.) ...    (2NFZ)