== Ontology Summit 2011 Communiqué: == = Making the Case for Ontology = ''(take 3)'' == Background == The theme of this year’s Ontology Summit is "Making the Case for Ontology": how, where and why ontology can be effectively deployed. This communiqué summarizes the consensus of participants in this year's summit on ways of making the case.. == Introduction == Anyone who knows the value of ontology also knows the "blank stares" of people who don’t. This communiqué provides tips, guidelines, and strategies for making the case to a variety of stakeholders. === Know who to target: === #Early adopters and the cutting edge, #Anyone facing problems that a good ontology can solve. === Establish Relevance: === #Focus on the value to the stakeholder, not the technology. #Show how and why an ontology can add value. #Relate the benefits to the stakeholder’s situation. === Generate excitement and instill confidence: === #Present success stories of ontology in use today. #Cite cases that are similar to what the stakeholder faces. #Explain the goals for the short, medium and long term. === Communicate clearly and with intent: === #Start with concrete examples, not abstractions. #Tailor the approach to different stakeholders. #Be ready with one liners and elevator speeches. #Focus on the outcome you’re trying to achieve. The goal of the 2011 Ontology Summit was to support these points. This communique distills and presents the key findings. The activities were divided into five tracks: case studies, ontology usage framework, value metrics, grand challenges, and strategy. The foundation is built on Case Sudies that demonstrate current uses of ontology. They provide a set of common problems that ontologies can be used for and value propositions. This helps identify who to target for making the case and for establishing relevance with a particular stakeholder. They generate excitement and instill confidence because stakeholders can see that it can work for them too. They provide a wide variety of situations, making it possible to develop a variety of approaches suited to different stakeholders. To successfully make the case for ontology, you need to be familiar with a wide variety of case studies. Mills Davis and Mike Bennett headed up this track. In order to better communicate case studies, we needed a good way to understand, classify, compare and contrast them. To this end, there was a track that created an Ontology Usage Framework (led by Michael Gruninger, Michael Uschold and Nicola Guarino). For any given case study, you want to be able to summarize its key aspects. These include: what is the function of the ontology, target users, and the value that the ontology gave. See (link) for details. Some main categories of ontology use case studies are: integration, decision support, and knowledge management. It is important to not get too wrapped up in the categories and the framework itself, but to use it as a communication tool. Because value is critically important to any stakeholder, a separate track was devoted to identifying various Value Metrics (led by Rex Brooks and Todd Schneider). Due to the diversity of functionalities and kinds of applications to be supported by ontology-based technologies, the value models and their metrics needed to make the case for ontology must be much more granular, less technically detailed and more case-specific than, for example, metrics already employed in software development. Metrics need to be focused on the particular business problem(s) for which the ontologies are to be applied. This track sets out a value paradigm for those promoting the use of ontologies. Five key areas were identified: IT efficiency, Operational efficiency, Business Agility, Business Efficiency and Customer Satisfaction. The above three focus areas address the here and now, what can be done in the near and medium term. A fourth track was devoted to exploring longer term idea that may require further research, but which are feasible nevertheless. This was the Grand Challenges track (led by Ram Sriram, Ernie Lucier and Alden Dima). Finally, there was an over-arching track for Strategy (championed by Matthew West and Peter Yim). How to put together all the materials gathered and present them in the most effective way to the appropriate stakeholder? I highlight two of the results that emerged from this track. First, the realization that the message needs to be adapted in different ways to different audiences. For example, the goal in talking to a budget holder is to get the work funded. Value is key. A more technical approach is required when talking to technologists. Next, one of the most interesting results of this track was a set of sound bites and elevator speeches gathered by the community. In analyzing all these, four themes emerged: ''Ontology as a new paradigm -'' "Ontology does for machines what the World Wide Web did for people." Steve Ray ''Ontology as a way of clarifying meaning -'' "The secret to making a good movie is getting everyone to make the same movie." So it is with enterprises and that's what ontologies do.' Jack Ring ''Ontology as a way to improve agility and flexibility -'' "There are three main things that ontologies are good for: flexibility, flexibility and flexibility" Michael Uschold ''Ontology as a way to improve interoperability and integration -'' "Ontology enables semantic interoperability by presenting information consistently across organizations and domains and machines" Cory Casanave In summary there were 5 tracks: Case Studies, Ontology Usage Framework, Value Metrics, Strategy and Grand Challenges. In the rest of the communique, we will highlight some of the more important conclusions from the tracks and email discussions. This will also elaborate a bit more on the four main themes above. In doing so, some of the tracks will be touched on more than others. Please refer to the track links for further information. == Key Themes == === Where and how are ontologies already being applied and delivering value? === The short answer is just about everywhere you look. In addition to the twenty reference case examples, the summit explored a broad range of consumer, social, enterprise, and systemic applications where ontologies are being used, for example to: * Provide and secure dynamic infrastructures where information of very different kinds is being combined from different sources on a large scale * Augment knowledge worker insights and decision-making as well as application-relevant semantics and business rules in off-the-shelf commercial software * Understand speech, written and visual language, and inter-semiotics of different kinds of information * Add intelligence to the user interface to provide new capabilities and enhanced user experience * Apply machine-learning, data-mining and other scale-based automatic techniques for the semantic document processing and advanced analytics in fields such as law, medicine, science, defense, and intelligence * Enable high-productivity, knowledge-driven collaborative work processes * Accelerate knowledge-intensive activities such as modeling & simulation, acquisition, design, and engineering * Power mission-critical processes in energy, financial services, logistics, manufacturing, and transportation. * Manage networks providing diagnostics, logistics, planning, scheduling, cyber-security, and event-driven process orchestration * Support adaptive, autonomic, & autonomous processes such as robotics, intelligent systems, and smart infrastructure * Assess risk and compliance in policy-driven processes such as exceptions, fraud, case management, predictive analytics, and emergency response, * Build systems that know, learn, adapt & reason as people do such as e-learning, tutors, advisors, cognitive agents, and smart social games. It is important to know about this variety, but it is perhaps more important to realize that most of it all boils down to three simple things: #getting everyone on the same page, #flexibility/agility #interoperability/integration Fundamentally, ontology is about getting agreements on what things mean. In an enterprise, it represents a radically different way to express meaning. The usual way is for meaning to be scattered randomly throughout the organization in people’s heads, in email, in no-longer-maintained requirements documents, in conceptual models etc. In computational artifacts, a lot of meaning is in the names used to refer to things: code, variables, data base schema. Ontology both forces and enables an organization to be clear about what things mean and in doing so, gets everyone on the same page. Clarifying meaning is one important vehicle for achieving interoperability and integration, which in turn, is a key vehicle for achieving flexibility. When no-one knows on what anything means and there are so many systems that are in production, you are stuck like the man in the figure. Ontology is the key to freeing this man, the key to flexibility, the key to enabling a company to do the same things more efficiently, and the ability to do entirely new things that were never possible before. It all goes back to ontology as a way to clarify and agree on meaning. May Ontology Set you Free! == Conclusions == We note that the discussion during this year’s Summit has focused on making the case for ontology projects within a business context where there is a financial justification for the use of ontology. However, there is also a case to be made for ontology research and the determination and pursuit of research goals for a case to be made for. The Grand Challenges track may address this, but it has not generally been addressed elsewhere. Generally, the approach in this summit has been pragmatic, emphasising the need to "put food on the table" but, as emphasised above, a fundamental benefit of adopting ontological approaches from the outset is that frameworks can grow to keep up with the reasoning and interoperability demands being made of them. == Acknowledgements == ---- = APPENDIX = Further Reading. This section summarizes and provides links to the key output of the tracks. This is source material that you may leverage when making the case for ontology. == Strategy == Ontology Usage Framework Value Metrics and Models == ISSUES and COMMENTS == '''Editors and track chairs: please add to this list! If you make a change in the document, and clearly mark it, as below.''' -MichaelUschold TODO: #example of a done task [--done/2011.04.14-18:20 MichaelUschold] #add links to the substantial body of work produced by the tracks. #add a few cases studies presented in table form from the longer list. Pick 2 or 3 key ones that: :a. were critically dependent on an ontology for success :b. clearly added value along the lines of flexibility and/or interoperability/integration, and or getting everyone on the same page Here are a few things that I would have liked to include or emphasize more. Ideas are welcome. * grand challenges and research * the role of inference * the usage framework, it kind of got short shrift,but maybe that is ok because it is so abstract? * highlight the importance with examples of explaining the value of an ontology in technical terms so that one can easily see what the role of the ontology was in the architecture of the system, what specific functionality ig gave, and how that led to the benefits * I did not include the nice paragraph from the original strategy contribution about ‘the core contribution of ontology’ I kind of went in a define direction, but i want to bring this back in somehow. It was about decision making. It is related to inference, perhaps these two can be covered together?