luigi@nifty
23 de noviembre de 2020
The goal of the NGI initiative is to help in shaping the development of an Internet more reflecting fundamental needs of trust, security, and inclusion.
A global knowledge ecosystem is one foundational layer to organise complexity and reveal transparency over data, and graphs are one of the technologies that best allow complex queries and uncover hidden patterns.
One side, graph databases are gaining more and more popularity:
https://www.forbes.com/sites/cognitiveworld/2019/07/18/graph-databases-go-mainstream/?sh=3c22b31b179d
For a comparison among different solutions:
https://db-engines.com/en/ranking_trend/graph+dbms
Aside of graph databases, graph analytics solutions are a second aspects for exploring relationships between entities of interest such as an internet of "people" that, with an analogy on graphs, could be seen as transactions (edges) between people, organisations, ideas, products and, more generally, entities (nodes).
Graph analytics was included as top 10 tech trends last year:
https://www.gartner.com/en/newsroom/press-releases/2019-02-18-gartner-identifies-top-10-data-and-analytics-technolo
We are assisting also at a combination between knowledge graph engineering and artificial intelligence - particularly AI applied on graphs.
Knowledge graph engineering has been used to describe concepts like semantic web and ontologies - a priori descriptions of the relationships in a databases. Wikidata is an example.
Artificial Intelligence in the realm of knowledge discovery has been being used for tasks like link predictions and research of how entities "signals" between each other.
Applications are used with success in fields like big-pharma (like in polypharmacy, to study the interaction of a drugs with others medicines and genes).
It is expected to create value also in applications for studying a better interactions between people, organisation, and working tasks - in a way, we could frame an "internet of people" like an optimisation function to maximise return of working activities in a way that is objectively human centric - up to us (or to a company pitching for human centrism) to transparently reveal what objective is (or the weights against which an AI system will optimise).
If of interest to know more about knowledge graphs and artificial intelligence meeting knowledge networks, an upcoming conference will focus on
Connecting data, people, and ideas.
It is a follow up of an initiative hosted by Columbia University, and has a community that rapidly increased to about a thousands members since a first conference held in May 2020 (that was backed by Accenture and UN).
https://www.knowledgegraph.tech/
I invite to take a look - date 2nd December
https://www.knowledgeconnexions.world/
For info about the content and participant, you can refer to the key person who nurtured the ecosystem of "people" and speakers:
Ellie Young, Head of Community KGC.
#pr-communications #productivity #information-technology #social-enterprise #data-analytics
