ISO 15926

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The ISO 15926 is a standard for data integration, sharing, exchange, and hand-over between computer systems.

Contents

The title, "Industrial automation systems and integration—Integration of life-cycle data for process plants including oil and gas production facilities", is regarded too narrow by the present ISO 15926 developers. Having developed a generic data model and reference data library for process plants, it turned out that this subject is already so wide, that actually any state information may be modelled with it.

History

In 1991 a European Union ESPRIT-, named ProcessBase, started. The focus of this research project was to develop a data model for lifecycle information of a facility that would suit the requirements of the process industries. At the time that the project duration had elapsed, a consortium of companies involved in the process industries had been established: EPISTLE (European Process Industries STEP Technical Liaison Executive). Initially individual companies were members, but later this changed into a situation where three national consortia were the only members: PISTEP (UK), POSC/Caesar (Norway), and USPI-NL (Netherlands). (later PISTEP merged into POSC/Caesar, and USPI-NL was renamed to USPI).

EPISTLE took over the work of the ProcessBase project. Initially this work involved a standard called ISO 10303-221 (referred to as "STEP AP221"). In that AP221 we saw, for the first time, an Annex M with a list of standard instances of the AP221 data model, including types of objects. These standard instances would be for reference and would act as a knowledge base with knowledge about the types of objects. In the early nineties EPISTLE started an activity to extend Annex M to become a library of such object classes and their relationships: STEPlib. In the STEPlib activities a group of approx. 100 domain experts from all three member consortia, spread over the various expertises (e.g. Electrical, Piping, Rotating equipment, etc.), worked together to define the "core classes".

The development of STEPlib was extended with many additional classes and relationships between classes and published as Open source data. Furthermore, the concepts and relation types from the AP221 and ISO 15926-2 data models were also added to the STEPlib dictionary. This resulted in the development of Gellish English, whereas STEPlib became the Gellish English dictionary. Gellish English is a structured subset of natural English and is a modeling language suitable for knowledge modeling, product modeling and data exchange. It differs from conventional modeling languages (meta languages) as used in information technology as it not only defines generic concepts, but also includes an English dictionary. The semantic expression capability of Gellish English was significantly increased by extending the number of relation types that can be used to express knowledge and information.

For modelling-technical reasons POSC/Caesar proposed another standard than ISO 10303, called ISO 15926. EPISTLE (and ISO) supported that proposal, and continued the modelling work, thereby writing Part 2 of ISO 15926. This Part 2 has official ISO IS (International Standard) status since 2003.

POSC/Caesar started to put together their own RDL (Reference Data Library). They added many specialized classes, for example for ANSI (American National Standards Institute) pipe and pipe fittings. Meanwhile, STEPlib continued its existence, mainly driven by some members of USPI. Since it was clear that it was not in the interest of the industry to have two libraries for, in essence, the same set of classes, the Management Board of EPISTLE decided that the core classes of the two libraries shall be merged into Part 4 of ISO 15926. This merging process has been finished. Part 4 should act as reference data for part 2 of ISO 15926 as well as for ISO 10303-221 and replaced its Annex M. On June 5, 2007 ISO 15926-4 was signed off as a TS (Technical Specification).

In 1999 the work on an earlier version of Part 7 started. Initially this was based on XML Schema (the only useful W3C Recommendation available then), but when Web Ontology Language (OWL) became available it was clear that provided a far more suitable environment for Part 7. Part 7 passed the first ISO ballot by the end of 2005, and an implementation project started. A formal ballot for TS (Technical Specification) was planned for December 2007. However, it was decided then to split Part 7 into more than one part, because the scope was too wide.

Need for ISO15926

In 2004, the National Institute of Science and Technology (NIST) released a report on the impact of the lack of digital interoperability in the capital projects industry. They pegged the cost of inadequate interoperability to be $5.8 billion per year. The full report is over 200 pages. [1]

The standard

ISO 15926 has thirteen parts (as of February 2022):

Description

The model and the library are suitable for representing lifecycle information about technical installations and their components.

They can also be used for defining the terms used in product catalogs in e-commerce. Another, more limited, use of the standard is as a reference classification for harmonization purposes between shared databases and product catalogues that are not based on ISO 15926.

The purpose of ISO 15926 is to provide a Lingua Franca for computer systems, thereby integrating the information produced by them. Although set up for the process industries with large projects involving many parties, and involving plant operations and maintenance lasting decades, the technology can be used by anyone willing to set up a proper vocabulary of reference data in line with Part 4.

In Part 7 the concept of Templates is introduced. These are semantic constructs, using Part 2 entities, that represent a small piece of information. These constructs then are mapped to more efficient classes of n-ary relations that interlink the Nodes that are involved in the represented information.

In Part 8 the Part 7 Templates are defined in OWL and instantiated in RDF. For validation and reasoning purposes all are represented in First-Order Logic as well.

In Part 9 these Node and Template instances are stored in an RDF triple store, set up to a standard schema and an API. Each participating computer system maps its data from its internal format to such ISO-standard Node and Template instances.

Data can be "handed over" from one triple store to another in cases where data custodianship is handed over (e.g. from a contractor to a plant owner, or from a manufacturer to the owners of the manufactured goods). Hand-over can be for a part of all data, whilst maintaining full referential integrity.

Documents are user-definable. They are defined in XML Schema and they are, in essence, only a structure containing cells that make reference to instances of Templates. This represents a view on all lifecycle data: since the data model is a 4D (space-time) model, it is possible to present the data that was valid at any given point in time, thus providing a true historical record. It is expected that this will be used for Knowledge Mining.

Data can be queried by means of SPARQL. In any implementation a restricted number of triple stores can be involved, with different access rights. This is done by means of creating a CPF Server (= Confederation of Participating Façades). An Ontology Browser allows for access to one or more triple stores in a given CPF, depending on the access rights.

Projects and applications

There are a number of projects working on the extension of the ISO 15926 standard in different application areas.

Capital-intensive projects

Within the application of Capital Intensive projects, some cooperating implementation projects are running:

Finalised projects include:

Upstream Oil and Gas industry

The Norwegian Oil Industry Association (OLF) has decided to use ISO 15926 (also known as the Oil and Gas Ontology) as the instrument for integrating data across disciplines and business domains for the Upstream Oil and Gas industry. It is seen as one of the enablers of what has been called the next (or second) generation of Integrated operations, where a better integration across companies is the goal. [5]

The following projects are currently running (May 2009):

Finalised projects include:

Some technical background

One of the main requirements was (and still is) that the scope of the data model covers the entire lifecycle of a facility (e.g. oil refinery) and its components (e.g. pipes, pumps and their parts, etc.). Since such a facility over such a long time entails many different types of activities on a myriad of different objects it became clear that a generic and data-driven data model would be required.

A simple example will illustrate this. There are thousands of different types of physical objects in a facility (pumps, compressors, pipes, instruments, fluids, etc). Each of these has many properties. If all combinations would be modelled in a "hard-coded" fashion, the number of combinations would be staggering, and unmanageable.

The solution is a "template" that represents the semantics of: "This object has a property of X yyyy" (where yyyy is the unit of measure). Any instance of that template refers to the applicable reference data:

Without being able to make reference to those classes, via the Internet, it will be impossible to express this information.

Related Research Articles

A standard data model is a data model that is widely used in a particular industry. The use of standard data models gives heterogeneous organizations a standard vocabulary and pre-negotiated semantics, format, and quality standards for data, which allows easier and faster information exchange. Standards are often defined by standards bodies or technology companies.

A modeling language is any artificial language that can be used to express data, information or knowledge or systems in a structure that is defined by a consistent set of rules. The rules are used for interpretation of the meaning of components in the structure of a programming language.

<span class="mw-page-title-main">Data modeling</span> Creating a model of the data in a system

Data modeling in software engineering is the process of creating a data model for an information system by applying certain formal techniques. It may be applied as part of broader Model-driven engineering (MDE) concept.

The Industry Foundation Classes (IFC) is a CAD data exchange data schema intended for description of architectural, building and construction industry data.

ISO 10303 is an ISO standard for the computer-interpretable representation and exchange of product manufacturing information. It is an ASCII-based format. Its official title is: Automation systems and integration — Product data representation and exchange. It is known informally as "STEP", which stands for "Standard for the Exchange of Product model data". ISO 10303 can represent 3D objects in Computer-aided design (CAD) and related information.

STEP-file is a widely used data exchange form of STEP. ISO 10303 can represent 3D objects in computer-aided design (CAD) and related information. Due to its ASCII structure, a STEP-file is easy to read, with typically one instance per line. The format of a STEP-file is defined in ISO 10303-21 Clear Text Encoding of the Exchange Structure.

ISO 10303-22 is a part of the implementation methods of STEP with the official title Standard data access interface or simply SDAI.

<span class="mw-page-title-main">Information model</span>

An information model in software engineering is a representation of concepts and the relationships, constraints, rules, and operations to specify data semantics for a chosen domain of discourse. Typically it specifies relations between kinds of things, but may also include relations with individual things. It can provide sharable, stable, and organized structure of information requirements or knowledge for the domain context.

In information science, an upper ontology is an ontology that consists of very general terms that are common across all domains. An important function of an upper ontology is to support broad semantic interoperability among a large number of domain-specific ontologies by providing a common starting point for the formulation of definitions. Terms in the domain ontology are ranked under the terms in the upper ontology, e.g., the upper ontology classes are superclasses or supersets of all the classes in the domain ontologies.

Gellish is an ontology language for data storage and communication, designed and developed by Andries van Renssen since mid-1990s. It started out as an engineering modeling language but evolved into a universal and extendable conceptual data modeling language with general applications. Because it includes domain-specific terminology and definitions, it is also a semantic data modelling language and the Gellish modeling methodology is a member of the family of semantic modeling methodologies.

The official title of ISO 13584 is Industrial automation systems and integration - Parts library, with the acronym PLIB. PLIB is developed and maintained by the ISO technical committee TC 184, Technical Industrial automation systems and integration, sub-committee SC4 Industrial data. See also ISO 10303.

Data exchange is the process of taking data structured under a source schema and transforming it into a target schema, so that the target data is an accurate representation of the source data. Data exchange allows data to be shared between different computer programs.

The ISO 15926 is an interoperability standard in the process industry. ISO 15926 includes the Work in Progress (WIP) database. WIP is available online and includes technical class descriptions of all the main equipment items, pipe, instruments, buildings, activities and anything else used in engineering, constructing, procuring, operating and maintaining process facilities.

Plant lifecycle management (PLM) is the process of managing an industrial facility's data and information throughout its lifetime. Plant lifecycle management differs from product lifecycle management by its primary focus on the integration of logical, physical and technical plant data in a combined plant model.

<span class="mw-page-title-main">Semantic data model</span> Database model

A semantic data model (SDM) is a high-level semantics-based database description and structuring formalism for databases. This database model is designed to capture more of the meaning of an application environment than is possible with contemporary database models. An SDM specification describes a database in terms of the kinds of entities that exist in the application environment, the classifications and groupings of those entities, and the structural interconnections among them. SDM provides a collection of high-level modeling primitives to capture the semantics of an application environment. By accommodating derived information in a database structural specification, SDM allows the same information to be viewed in several ways; this makes it possible to directly accommodate the variety of needs and processing requirements typically present in database applications. The design of the present SDM is based on our experience in using a preliminary version of it. SDM is designed to enhance the effectiveness and usability of database systems. An SDM database description can serve as a formal specification and documentation tool for a database; it can provide a basis for supporting a variety of powerful user interface facilities, it can serve as a conceptual database model in the database design process; and, it can be used as the database model for a new kind of database management system.

<span class="mw-page-title-main">Generic data model</span>

Generic data models are generalizations of conventional data models. They define standardised general relation types, together with the kinds of things that may be related by such a relation type.

ISO/TC 184/SC 4 is an international standards organization responsible for industrial data. ISO/TC 184/SC 4 develops and maintains ISO standards that describe and manage industrial product data throughout the life of the product. ISO/TC 184/SC 4, Industrial data, is Subcommittee 4 of ISO/TC 184, Automation systems and integration, which is Technical Committee 184 of the International Organization for Standardization (ISO).

<span class="mw-page-title-main">Integrated Operations in the High North</span>

Integrated Operations in the High North is a unique collaboration project that during a four-year period starting May 2008 is working on designing, implementing and testing a Digital Platform for what in the upstream oil and gas industry is called the next or second generation of Integrated Operations. The work on the Digital platform is focussed on capture, transfer and integration of real-time data from the remote production installations to the decision makers. A risk evaluation across the whole chain is also included. The platform is based on open standards and enables a higher degree of interoperability. Requirements for the digital platform come from use cases defined within the Drilling and Completion, Reservoir and Production and Operations and Maintenance domains. The platform will subsequently be demonstrated through pilots within these three domains.

Energistics is a global, non-profit, industry consortium that facilitates an inclusive user community for the development, adoption and maintenance of collaborative, open standards for the energy industry in general and specifically for oil and gas exploration and production.

POSC Caesar Association (PCA) is an international, open, not-for-profit, member organization that promotes the development of open specifications to be used as standards for enabling the interoperability of data, software and related matters.

References

  1. ↑ "ISO15926HowTo_EntryPoints – POSC Caesar – Trac".
  2. ↑ url=https://15926.org/topics/part2/ECM4.5.1/lifecycle_integration_schema.html
  3. ↑ "Archived copy" (PDF). Archived from the original (PDF) on 2015-09-24. Retrieved 2015-04-13.{{cite web}}: CS1 maint: archived copy as title (link)
  4. ↑ "Demo for the EDRC Use Case 2 (Manufacturer's side) - DATA INTEGRATION STANDARD ISO 15926 - TechInvestLab.ru". Archived from the original on 2016-03-04. Retrieved 2015-04-13.
  5. ↑ The Norwegian Oil Industry Association (OLF). "Integrated Operations and the Oil and Gas Ontology" (PDF). Retrieved 2009-05-06.
  6. ↑ "E P I M". www.epim.no. Archived from the original on 25 July 2009. Retrieved 11 January 2022.
  7. ↑ Norwegian Petroleum Directorate. "Drilling Reporting to the authorities". Archived from the original on 2009-07-26. Retrieved 2009-05-05.
  8. ↑ "Petroleumstilsynet - Main page". www.ptil.no. Archived from the original on 15 April 2009. Retrieved 11 January 2022.
  9. ↑ "Facts about Åsgard". www.statoilhydro.com. Archived from the original on 23 April 2009. Retrieved 11 January 2022.
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