Ontologies in the Context of Cloud Computing and Big Data

Transcription

1 Ontologies in the Context of Cloud Computing and Big Data Ontologies and Conceptual Models for Industrial Enterprises Group INGAR (CONICET UTN) INTEC (CONICET UNL) Santa Fe - Argentina

2 Nowadays Context Product customization Short Product Lifecycles with extremely short time-to-markets Product development processes & manufacturing operations are distributed over the globe Global businesses entered a new era of decision making in which the ability to gather, store, access, and analyze enormous amounts of data has grown exponentially The success of global manufacturing enterprises depends upon the entire worldwide integration of many stakeholders working on collaborative decision-making processes Collaborative Manufacturing Collaborative Supply Chain

3 Collaborative Manufacturing Collaborative Environment Requires synchronization across a broad scope of manufacturing activities performed by multiple organizations that generate and exchange enormous amounts of heterogeneous data (different syntaxes, distinct semantics, various granularities and time-frames)

4 Collaborative Supply Chains Suppliers Producers Deposits & Warehouses Producers Distribution Centers Retailers Customers Collaborative business process Collaborative business process Source Make Deliver Source Make Deliver Many companies (suppliers suppliers, manufacturers, clients, 3PLS, 4PLs, etc.) aligned into collaborative business process. Globally integrated versus linear and silo-oriented SCs.

5 Collaborative Supply Chains Supplier s Supplier Supplier Design, planify and operate Enterprise Design, planify and operate Customer Design, planify and operate Final Customer Source Data Make Data Deliver Vertical integration: Different time scales and information granularities Horizontal integration: Same layer applications 5

6 Smart Manufacturing according to the SMLC Group ( Smart Manufacturing Leadership Coalition ) CEP Journal, October 2012

7 Smart Manufacturing

8 Smart Manufacturing

9 Smart Manufacturing

10 Smart Manufacturing

11 Smart Manufacturing

12 Smart Manufacturing

13 Smart Manufacturing

14 Factories of the Future Use of cloud-based platforms to capture knowledge and manage rules Cloud-based platforms in high tech manufacturing Cloud-based marketing automation applications to plan, execute and track results of every campaign Cloud-based Human Resource Management (HRM) systems to unify all manufacturing locations globally

15 Factories of the Future Manufacturers rely on cloud-based systems to streamline key areas of their business: marketing, design, manufacture, automation, supply, etc. SW CW PW Cloud efficient supply Service World Cloud-based engineering Computational World Cloud-based automation Physical World Rolf Riemenscheider, European Commission, APMS 2012

16 Nowadays Context Supplier s Supplier Supplier Design, planify and operate Enterprise Design, planify and operate Customer Design, planify and operate Final Customer Source Make Deliver Collaborative Supply Chain and Collaborative Manufacturing lead to complex systems that resort to Cloud Computing and Big Systems technologies

17 WhyOntologies ntologiesin thecontext of Cloud Computing and Big Systems? Can we continue designing cloud-based data services in the same way that we do in traditional systems? How to articulate huge amounts of data (with different syntaxes and semantics) of several partners that need to collaborate? How to provide structure to unstructured data?.?

18 An annual series of events that involves the ontology community and communities related to each year's theme chosen for the summit. Co-organized by: Ontology Summit Series Ontolog, NIST (US National Institute of Standards and Technology) NCOR (US National Center for Ontological Research ), NCBO (National Center for Biomedical Ontology) IAOA (International Association for Ontology and its Applications) NCO_NITRD (National Coordination office for the Networking and Information Technology Research and Development) Activities: 3 months of virtual discourse (over our archived mailing lists) and virtual panel sessions (over augmented conference calls) 2-day face-to-face symposium Main Deliverable: Ontology Summit 201x communiqué

19 Ontology Summit Series Ontology for Big Systems Ontology Summit 2012 explored the current and potential uses of ontology, its methods and paradigms, in big systems and big data. Key questions What can ontology provide to support and understand Big Systems? How does ontology provide that? How does the science and engineering of Big Systems impact ontology? Organization: Big systems engineering Big data challenge Large scale domain applications Cross track 1 Quality Cross track 2 Federation and integration of systems Big data, complex techno-socio-economic systems, intelligent or smart systems, cloud computing, and collective intelligence:

20 Ontology Summit 2012 Ontology for Big Systems Big systems engineering to describe physical systems, Engineers have always built models to specify products to be built, to describe system interaction with the world. They serve as the ground truth for design and analysis in that they are the authoritative source of information. They carry an (often implicit) ontology, expressing a theory or a set of assumptions, about the world or some part of it. Modeling languages need a precise meaning to enable collaboration, standards, and reasoning. This is where ontology comes in

21 Ontology Summit 2012 Big Data Applications Ontology for Big Systems understand the data garner information and knowledge from it, intelligently combine it with other data sets To efficiently do this We need to be able to represent the assumptions and conceptualizations that underpin knowledge in those domains. Data creators and publishers need to make explicit what their data represents together with the context of the data and its creation.

22 Ontology Summit 2012 Ontology for Big Systems Ontologies and ontological analysis are vital parts of a solution addressing the problems of architecting and engineering big systems and big data. Ontologies can be used to: Make explicit and accessible the vital assumptions about the nature and structure of engineered systems and their components. Help people better understand and disentangle the complexity of big engineered systems and their social, economic and natural environment Enable integration among systems and data through semantic interoperability.

23 Ontology Summit 2012 Ontologies can be used to: (cont.) Ontology for Big Systems Improve models and modeling, their adaptability and reuse, and resulting design. Enhance decision-support systems. Aid in knowledge management and discovery. Provide a basis for more adaptable systems More details in:

24 Group Research Experience Development of conceptual models and domain ontologies in the fields of industrial enterprises and software development processes: Supply Chain ONTOlogy (SCOnto) PRoduct ONTOlogy (PROnto) Scheduling Ontology (SchedOnto) Collaborative Model for capturing and representing the engineering Design process (CoMoDe)

25 Thank you very much for your kind attention!! Silvio Gonnet Gabriela Henning Horacio Leone Luciana Roldán Marcela Vegetti Questions?