digital transformation
The Digital Transformation of Knowledge Management
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The fundamental purpose of implementing the new paradigm for artificial intelligence in organisations is the Digital Transformation of knowledge management. Digital Transformation inherently entails the effective acceleration of knowledge transmission among professionals, the increase and enrichment of interconnections and synergy among them, and the generation of new knowledge, ideas, and problem-solving models. All of this takes places within a social-digital framework that impulses creativity and inventiveness, and thus the collective creation of value for the organisation, both as a whole and for each person it comprises.
Knowledge management combines development and learning, moulding them into contextual, adaptive processes. For this to happen, the system must be comprehensively modelled from an anticipatory perspective that maximises learning efficiency and, consequently, its acceleration, both from an individual professional perspective and as departments, units, work centres, or any other type of aggregate. The system, then, must meet the needs of an adaptive learning paradigm and ultimately be able to intelligently make recommendations on content; in short, personalised learning.
More intelligent relations that are more useful
The GNOSS Cognitive Platform can convert documents into Linked Data represented according to Semantic Web standards. Once consolidated in a searchable Knowledge Graph that systems can interpret, the data can be structured according to Linked Data Web principles.
Together with natural language processing, these platform capacities make the relationships between the system and its users more meaningful through conversation and context, and therefore more useful and more intelligent.
The Metasearch Engine, a general point of access to knowledge assets
Semantic Technology provides a metasearch engine or general point of access to the organisation’s entire range of private and knowledge assets. This opens up access to the following benefits:
- - Integrate the entire organisation’s work
- - Build an inventive and creative framework: create knowledge more effectively
- - Uncover knowledge hidden in relationships and develop systems capable of querying and discovering knowledge
- - Improve access to knowledge and learn faster and more efficiently
- - Enrich interactions and communication: communicative interaction
Integrate the entire organisation’s work
- Link, integrate and unify the knowledge generation and creation processes with query and publication processes, dispensing with infomediaries, and thereby transforming the principal of transparency into a management principle which impulses each unit’s self-management and self-regulation, all the while empowering the people present where the problems (and the solutions) are. The essence of the solution consists of what the organisation as a whole has created across their knowledge areas.
- Optimise the use of this common knowledge base, enhancing the value of the ensemble of work across all areas of the organisation.
- Develop a sophisticated system user profile based on the semantic interpretation of the user’s digital footprint as they interact with the platform, enabling individualised communication among users according to their interests, aims and responsibilities.
Build an inventive and creative framework: create knowledge more effectively
- Represent data in concert with an expressive model that permits the use, re-use and linking of data with other data, no matter where either of them are.
- Deliver a powerful tool to user groups for creating, co-creating, editing and generating narratives, stories, collections and analytical documents.
- Contribute a means by which to enrich, integrate, link and relate contents, whether formal, informal, internal or external
Uncover knowledge hidden in relationships and develop systems capable of querying and discovering knowledge
- Provide a smarter, faster and more semantically conscious search and query experience where the search engine understands that when a user searches for [Nobel], they want results on [Alfred Nobel] and not the [Nobel Peace Prize].
- Develop the Graph’s query and visualisation modes and tailor them to diverse audiences. These models focus on maximising the satisfaction of user interests by suggesting data expressly related to the results whose answers fully answer their questions.
- Ensure a superior experience of knowledge discovery and navigation without the slightest deterioration on any type of device so that users are able to access the information that interests them and take the action they choose at any point in time or from any location
Improve access to knowledge and learn faster and more efficiently
- Supply relevant context for any piece of information - which therefore becomes enriched information - originating from both internal and external sources
- Offer personalised information based on predictive, adaptive and reliable recommendation systems that are founded on entity recognition and linking, and on a sophisticated profile that reflects people’s interests, activities and responsibilities.
- Access augmented writing and reading processes in real time thanks to the enrichment of any resource. This is achieved by recognition of the entities it contains and their main subject matter, as well as through their subsequent linking to entities and subjects from the system itself, or from third-party knowledge databases.
- Promote the construction of evolved searchable data visualisation systems on board with the possibilities semantic searching offers.
Enrich interactions and communication: communicative interaction
- Publish this knowledge in a manner suited to the interests and needs of varied internal and external audiences through the construction of themed websites based on data subsets or subgraphs that comply with specific requirements (Semantic Dynamic Publishing).
- Confer meaningful access for writers and communication teams to the information set, thus strengthening the organisation’s ability to build stories based on data. Potentially accelerate the latest news drafts.