Ontologies in the Context of Cloud Computing and Big Data

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Ontologies in the Context of

Cloud Computing and Big Data

Ontologies and Conceptual Models for

Industrial Enterprises Group

INGAR (CONICET – UTN) INTEC (CONICET – UNL)

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Nowadays Context

Product customization Short Product Lifecycles

with extremely short time-to-markets

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 Product development

processes & manufacturing operations are distributed over the globe

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

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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)

Collaborative Environment

Collaborative Manufacturing

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Suppliers Distribution Retailers Centers Customers Producers Deposits & Warehouses Producers Make Source Deliver Source Make Deliver

Collaborative business process

Many companies (suppliers’ suppliers, manufacturers, clients, 3PLS, 4PLs, etc.) aligned into collaborative business process.

Globally integrated versus linear and silo-oriented SCs.

Collaborative Supply Chains

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5 5

Design, planify and operate Make Source Deliver Enterprise Customer Supplier Supplier’s Supplier Final Customer Design, planify and operate

Design, planify and operate

Data Data

Horizontal integration: Same layer applications

Vertical integration:

Different time scales and information

granularities

Collaborative Supply Chains

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

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Smart Manufacturing

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Smart Manufacturing

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Smart Manufacturing

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Smart Manufacturing

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Smart Manufacturing

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Smart Manufacturing

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Smart Manufacturing

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Factories of the Future

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 Use of cloud-based platforms to capture knowledge and manage rules

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Factories of the Future

SW

CW PW

Cloud efficient supply – Service World

Cloud-based engineering – Computational World Cloud-based automation – Physical World

Manufacturers rely on cloud-based systems to streamline key areas of their business: marketing, design, manufacture, automation, supply, etc.

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Nowadays Context

Design, planify and operate Make Source Deliver Enterprise Customer Supplier Supplier’s Supplier Final Customer Design, planify and operate

Design, planify and operate

Collaborative Supply Chain and Collaborative Manufacturing lead to complex systems that resort to Cloud Computing and Big Systems technologies

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Why O

O

Ontologies

ntologies

ntologies in the context

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?

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An annual series of events that involves the ontology community and

communities related to each year's theme chosen for the summit

.

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)

Co-organized by:

Activities:

Main Deliverable: Ontology Summit 201x communiqué 2-day face-to-face symposium

3 months of

virtual discourse (over our archived mailing lists) and virtual panel sessions (over augmented conference calls)

Ontology Summit

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Ontology Summit

Ontology Summit Series

Series

Ontology Summit 2012 explored the current and potential uses of ontology, its methods and paradigms, in big systems and big data.

Ontology for Big Systems - 2012

Organization:

• Big systems engineering

• Big data challenge

• Large scale domain applications

• Cross track 1 – Quality

• Cross track 2 – Federation and integration of systems

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?

Key questions

Big data, complex techno-socio-economic systems, intelligent or smart systems, cloud computing, and collective intelligence:

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Ontology Summit

Ontology Summit 2012

2012

Ontology for Big Systems

Big systems engineering

They serve as the ground truth for design and analysis in that they are the authoritative source of information.

Engineers have always built

models

to specify products to be built, to describe physical systems,

to describe system interaction with the world.

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

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Ontology for Big Systems

Data creators and publishers need to make explicit what their data represents together with the context of the data and its creation.

Big Data Applications

intelligently combine it with other data sets understand the data

garner information and knowledge from it,

We need to be able to represent the assumptions and

conceptualizations that underpin knowledge in those domains. To efficiently do this

Ontology Summit

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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.

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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 Ontologies can be used to: (cont.)

Ontology Summit

2012

More details in:

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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)

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Thank you very much for your

kind attention!!

Silvio Gonnet [email protected] Gabriela Henning [email protected] Horacio Leone [email protected] Luciana Roldán [email protected] Marcela Vegetti [email protected]

Questions?