Flare’s Energy Industry Taxonomies
Comprising an integrated set of Taxonomies, there are over 36,000 major terms. The taxonomies are hierarchical and include aliases, synonyms and acronyms and over 450,000 relationships. Additional taxonomy terms are added as part of Flare’s ongoing development of the taxonomy scope.
In 2020, for the Oil and Gas industry a sub-set of approximately 60,000 well log curve names were added.
Developments for 2021 include the addition of an Acronyms module.
The scope of the Taxonomies is illustrated in the graph below,
Master/Reference Data Model
A flexible master/reference data model allows use of the pre-existing master data model, and creation of new master data types, attributes and relationships.
In Sirus or the Sirus API, standard names and valid values can be made instantly available to any application.
What you can do with Taxonomies
Flare has been developing its taxonomies since 2002. The reason this will always be a work-in-progress is that Taxonomies are so much more dynamic than a static list of terms. Used properly, taxonomies can model a business, represent the knowledge in a business, and be used to streamline and improve many information systems. And just as businesses and their terminology change, so do the taxonomies that describe them.
What you can do with Taxonomies
Taxonomy is the foundation of successful integration initiatives by providing normalised terms for context, asset and other taxonomy classes. This reduces integration effort across the entire application landscape.
Taxonomy can support classification tools with full automation or curated tagging of content. Properly tagged content is easy to manage.
By agreeing standard terms (a taxonomy) and ensuring that the standard terms are applied to content, it is easier to automate the handling of information, e.g. automation of a workflow or a records management policy.
Taxonomy improves search relevancy, precision and recall.
Hierarchical taxonomies enhance search refiners, facetted search and broad and narrow term searching.
Taxonomies can provision new visualisations and metrics. Taxonomies can support BI and Analytics.
Users or systems can search using the terms they are familiar with; the taxonomies provide the answer.
MDM systems store master and reference data, and Flare’s Sirus Graph allows this to happen at scale. The system allows modelling of Master Data Classes, management of the model and the values.
Records management can be automated by linking the records management policy to the Taxonomies.
Proper application of a taxonomic approach can reduce the amount of learning AI/ML applications need. Taxonomies support AI and natural language initiatives by providing human knowledge and structural thinking to support the applications. This means the AI/ML tools start with university rather than primary school level language.
Taxonomy normalises terms, to aid structuring, visualisation and clustering and analysis of content and data.
A Taxonomic approach enables the deployment of standard business glossaries and dictionaries. Ensuring standard terminology is consistent across an organisation enables better human to human communication and systems integration across multiple information sources.
Flare’s Sirus toolkit provides a pragmatic and scalable business glossary capability, allowing millions of terms to be defined, and accessible through an API.
A taxonomic approach allows non-digital assets (such as books, samples, people) and non-text digital assets (such as audio, video and images) to be tagged and indexed.
The Flare Taxonomies provide the most robust, comprehensive knowledge map of the E&P business available today. The Taxonomies are comprised of thousands of terms (valid values), relationships, synonyms and aliases to help E&P professionals tag, catalogue, publish and ultimately find their E&P information assets.
The Taxonomies can be licensed as a stand-alone product or integrated with other Sirus modules.
What is a taxonomy?
A taxonomy is a hierarchical list used for classifying things. The Flare Taxonomies are designed to classify all kinds of E&P information but additionally they are associated to one another to create rich semantic relationships between the elements. These business relationships make the Flare Taxonomies much more effective than a simple hierarchy with controlled vocabulary and provide a unique and powerful way to represent knowledge.
Asset classification – the asset taxonomy
Flare’s asset relationship taxonomy supports the business assets typically found in the E&P environment, such as wells, fields, licenses, and basins and is fully configurable to meet individual client requirements. For each asset the company standard name is used as well as aliases including industry names, UWIs and short names. The Catalog user interface allow users to browse and select these assets and utilises the inter-relationships between lists to subset the values displayed; e.g. selecting a country from the country list will limit the fields and wells displayed.
E&P classification – the contextual taxonomy
Flare’s E&P classification methodology is based on the concept of ‘Product Types’, the common information items created by people in the industry. To date over 6,000 product type values have been defined, each one being attributed with a unique name and, in many case, a number of aliases to facilitate searching, as well as defined relationships to other attributes in the taxonomies.
Each entry can contain industry aliases, company specific aliases, foreign aliases, acronyms and examples as well as its relationship to other values.
- Provides standard reference terms (values), with synonyms, for keywords, asset names and E&P deliverables to ensure long-term consistency and searchability of information
- Improves user search precision (accuracy of results) and recall (completeness of results)
- Underpins structured, metadata-driven metrics to measure what information items exist, what is missing and what does not exist
- Provides the structure to support auto-classification tools
- Provides an extensive framework for custom extensions and machine learning
- Is the result of more than 15 person years' work and has been used by thousands of E&P professionals
- Is significantly more cost-effective than developing a first-draft, in-house taxonomy
- Extensive coverage - of the E&P business
- Comprehensive - with more than 6,000 E&P products, 15,000 keywords and over 400,000 relationships
- Related hierarchical terms - including synonyms, acronyms and examples as well as disambiguation logic
- Client-specific terms - accommodated as aliases or as proprietary extensions to the standard taxonomies