Join the dots!
Knowledge is inferred using semantic & application metadata, structured by an ontology. Knowledge graphing applies probabilistic, automated reasoning to determine meaning from semantically-described content, through its context & relationship predicates as defined by a domain ontology, linking object & subject.
The ontology is an evolving neural web: mapping & ranking the inferred perspectives to cohere the organisational knowledge the querent is looking for. The growth mindset, which pushes the frontiers of human achievement, is fuelled by such knowledge: where human imagination & capability are augmented & automated by computer power, speed & logic.
Data, metadata & semantics foundations!
If you haven’t already achieved this, then take advantage of our data audit, data discovery & data quality services.
Second, does your data have gaps? Is the data is valid & canonical? Is any aggregation or consolidation needed? Again, if not, benefit from our experience in data transformation, data validation, & general data engineering services.
To help you, we offer metadata audit, metadata discovery, & the ability to significantly reduce the cost & effort of extracting metadata from opaque packaged applications (ERP & CRM).
Remedying metadata gaps still requires manual effort. Missing metadata will upset any Azure & Sharepoint deployments so its better to get into good habits early to benefit your overall digital capability.
Metadata in dark data, archives or legacy systems also requires consideration because it may still, even if unused, be within scope of data privacy & protection regulation & therefore an important part of your corporate knowledge- base.
Taxonomies also provide important metadata, but these are hierarchical, non-semantic & 2D, lacking the multi-dimensionality of perception (meaning, relationship & context).
So your organisation will need semantic metadata as well as the existing application descriptors (metadata).
We will help you source & organise the terms you actually use to refer to your organisational data & knowledge; to provide domain consistency & coherence.
The components of inferred, automated, reasoning i.e. knowledge system.
The choice of graph database depends on the individual use case plus other considerations such as memory efficiency, scale, end user devices & complexity.
So choosing the right GraphDB is best done with the help of experts.
The nodes are the key entities (objects & subjects – tuples or triples) of your information needs & the probabilistic comparative ranking (matrices or lists) per attributes based on relevancy.
As with BI, discovery interviews by an independent consultant can help to achieve consensus, embrace change & ensure the right approach is taken.
This involves surfacing & modelling information priorities; organisational semantics; the nature of those relationships & probable vocabulary (semantic tags).
The act of ‘joining the dots’ brings implied context & salience. As subjects & objects develop multiple relationships, the magic lies in graphing those as matrices, ranking the relationships as they pertain to search parameters.
Those ‘dots’ & their ‘joins’ indicate the indicate relationships & their degree of salience, just as they do in a search engine.
What you want your systems to do is enable meaningful, automated reasoning, so that searches provide the most relevant results (without significant omissions).
From a systems point of view, that reasoning has to be
machine-interpretable & probabilistic so as to provide inferred knowledge i.e. the whole being greater than the sum of the parts (which is currently how things are).
The database type which enables this is the knowledge graph.
Choose the optimal realisation path towards a future you can’t yet see.
This will also save you having to implement & fill your own Knowledge Graph database if you are not ready for this.
If you have a Knowledge Graph project already underway, why not save a lot of time & effort by using triples that others have already written. No need to reinvent the wheel for standard items right?
Here you benefit from help with:
With this strategic planning offering, companies, like Odin’s ravens, will be well placed to gain insight from both historical performance (the corporate memory) & having the capacity to think and analyse the real-time world around them, to see the future.