The OASIS Open Supplychain Information Modeling (OSIM) TC aims to standardize and promote information models about all aspects of supply chains. This involves two kinds of work:
- Identify value propositions and use cases for applying information modeling to existing supply chain activities.
- Develop information model artifacts for data used in these activities to promote harmonization and re-use.
The IM work products of the TC should address the following goals:
An Information Model (IM) defines the essential content of data artifacts used in computing, independently of how they are represented for communication or storage.
The core purpose of an IM is to define logical equivalence of data artifacts. An artifact is "an immutable blob of data" (**). Immutability means that artifacts are identified only by their value, and all instances of the same value are considered equivalent.
An information model defines the logical value of typed data such as primitives, structures, messages, and documents, allows logical values to be validated and compared for equality regardless of format, and enables hub-and-spoke lossless translation of data instances across formats.
- An abstract schema is the formal definition of essential content
- A logical value is the internal representation of essential content, defined by application behavior, independent of both data format and programming techniques
- When reading data instances into information values, essential content is validated and insignificant data is discarded
** Supply chain Levels for Software Artifacts
An information model includes encoding rules that define how information values are parsed from and serialized to messages in a specific data format. Data formats include:
- Text-based data languages, e.g., XML, JSON
- Binary data languages, e.g., CBOR, Protobuf
- Schemaless data structures, e.g., IP packets
Encoding rules may define more than one data format for a specific data language, e.g., fields represented as elements or attributes in XML, or object or array members in JSON.
An abstract schema is itself an information value, enabling it to be validated against a metaschema, losslessly translated across data formats, as well as defined without serialization using domain-specific language grammars and tools. Serializing a schema allows it to be bundled with the messages it defines for dynamic version tracking, and processed using language-specific tools and ecosystems.
Parenthesized terms are usable interchangeably in the context of information modeling.
Abstract schema: a definition of the essential content to be communicated or stored to serve a particular purpose
Data format (encoding rules, serialization rules): an identified mechanism for converting logical values to and from data values
Data value (artifact, document, lexical value, message): a sequence of text characters or octets (bytes) that represents a logical value in a data format
Information definition language: a domain-specific representation of abstract schema logical values
Information model: an abstract schema for a particular application plus a set of application-independent encoding rules
Logical type: an identified definition of a unit of essential content
Logical value (information value): the internal representation of an instance of a logical type that expresses its essential content
Metaschema: a schema that validates schemas for the language in which it is written, including itself
Presentation format: a view of logical values that does not necessarily preserve all essential content, for display or documentation purposes