Applying Standards to Information Centric Operations
We live in a world of information . From the moment we are born we are surrounded by shapes and sounds and color , and we spend the next few years figuring out what it all means . In our adult working lives , almost all of us live in information some of the time , and some of us all the time – whether it ’ s profit and loss figures , sales pipelines , engineering design specifications , software or whatever . Information is our natural habitat .
And yet , to interact with this sea of information in which we live , we must constantly hop from one computer application to another . Or in some cases do all our work within one application and use extra features they introduced to let us handle diagrams in a word processor , paragraph layouts in a spreadsheet and so on . The idea that we could spend our working lives within a single integrated information space (“ Cyberspace ,” to use William Gibson ’ s term for it in the novel Neuromancer 1 ) has continued to elude us , despite the writings of visionaries like Gibson and others like Douglas Adams 2 and Vannevar Bush as far back as 1945 [ 1 ].
Some of the pre-conditions for information-centric working are well into the early adopter stage of the technology evolution cycle . For example , the introduction of semantic models , along with the “ Data Centric ” Manifesto 3 are starting to provide the thinking , and more importantly the tools , to start the journey from here to there . A more complete inversion of applications and data does not require new technology but a different way of using the technology we already have ; a discontinuity in the technology adoption curve .
To complete that journey is going to require a combination of imagination , vision and standards .
This article explores the case for standards to support data-centricity , both for current uses in data centric operations and digital twins , and for future uses that may only become clear under a more ubiquitously information-centric way of working .
1 DATA CENTRICITY
The Data Centric revolution in computing [ 2 ] brings promises and challenges , separating content , semantics and presentation . This empowers data to be treated as a resource in its own right , with its own lifecycle , quality measures and ownership independent of the applications which use it and potentially outliving them . Use cases include increased flexibility , risk and regulatory compliance and the provision of datasets for training generative AI solutions . As a simple byproduct , firms providing semantically enabled data will also find a faster and smoother route towards FAIR ( Findable , Accessible , Interoperable , and Reusable ) data operations [ 3 ].
1
Gibson , W . ( 1984 ). Neuromancer . Ace . ISBN : 0-441-56956-0
2
Adams , D . ( 1990 ). Hyperland ( video in 5 parts ). Available : http :// www . youtube . com / v / rOsPKjbMvxY & hl = en & fs = 1 &
3
The Data Centric Manifesto . Available at http :// datacentricmanifesto . org / Journal of Innovation 13