Linking Distributed Data for a Human-Friendly Web

At the Linked Data-driven company of the near future:

1. You will find it curiously difficult to distinguish between “traditional” data workers (analysts, data scientists, etc.) and those in other functional areas who, at other companies, are less reliant on data. The agent of change here is the unambiguous way that Linked Data represents the world.

2. You will marvel at the volume and variety of data accruing from disparate sources, flowing from team to team, integrating with other data, producing unexpected insights, available to anyone at any time.

The data, for example, would be browseable and searchable by humans, crawlable and queryable by machines. Additionally, just like the Web, Linked Data enjoys a remarkable network effect in that each data set added to the network increases the incremental value of every data set in the network.

3. You will be inspired by the rapid creation and adjustment of models and automated processes in response to real-time data. Much of this agility is fueled by machine learning models being deployed at a far faster pace than can be achieved without the aid of Linked Data.

This is because the output of machine learning is tightly correlated with the quality of input data. People who work in this area spend much of their time cleaning and preparing input data, whereas semantically linked data has been “pre-understood” and embedded with knowledge.

[Now,] the energy devoted to the costliest, slowest phase of data work — preparation — can finally be reallocated to more productive activities like analysis.

Source: Techonomy

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