Definitions

Digitalisation is the ongoing integration of digital technologies and digitised data across the economy and society. The definitions below aim to familiarise the user with key concepts and terminologies applied in this digitalisation online resource.

Key concepts
3D printing/additive manufacturingAdvanced roboticsArtificial intelligence (AI) Autonomous vehicle
BlockchainDigitalisationDigitisationElectric vehicle
ICT-based mobile workIndustrial biotechnologyInternet of thingsPlatform  
Platform economyPlatform workVirtual reality (VR) and augmented reality (AR) 

 

3D printing/additive manufacturing 

Image of icon for 3D Printing
The process, performed by machines, of creating physical objects from three-dimensional digital models, generally by laying down successive layers of material. In manufacturing, the more common term is additive manufacturing (AM). The European Commission’s blueprint on AM defines it as

'a group of processes to build physical objects directly from 3D Computer-Aided Design (CAD) data. AM adds liquid, sheet, wire or other powdered materials to form component parts or products, usually in a layer-by-layer process (e.g. 3D-Printing) as opposed to subtractive manufacturing methodologies.'

The key prerequisite of 3D printing and AM is that products can be digitally modelled before being physically generated.

Reference documents:

Examples of application/use:

  • Used increasingly in a wide range of settings, including in prototyping and visual design in the automotive sector and many other sectors and the manufacture of orthodontics and prosthetic devices, aircraft parts, construction materials and jewellery, among other things. 

 

Advanced robotics

Image of icon for advanced robotics
The branch of robotics dedicated to the development of robots that, through the use of sensors and high-level and dynamic programming, can perform ‘smarter’ tasks, that is, tasks requiring more flexibility and accuracy than those of traditional industrial robots. 

The term applies to digitally enabled robots working within industrial environments that are equipped with advanced functionality, for example sensors that detect potential collisions and halt or perform a programmed motion very quickly. This advanced functionality allows robots to deal with less structured applications and, in many cases, collaborate with humans (instead of being segregated from them). 

The term ‘service robot’ is understood as any robotics application used for anything except manufacturing. The International Organization for Standardization (ISO) definition is

'a robot that performs useful tasks for humans or equipment excluding industrial automation applications’.

Examples of application/use:

  • Eve, the robot scientist, developed at the University of Manchester can speed up drug discovery by rapidly analysing different compounds for their suitability.
  • Ultraviolet (UV) disinfection robots can be used in settings with high infection risks, such as hospitals, to carry out cleaning tasks using UV light technology. 
  • Kaspar, the humanoid social robot, has been developed to support social interaction with autistic children.
  • Robotnik mobile service robots can carry out complex lifting and moving tasks with high levels of awareness of their environment, which helps, for example, to prevent collisions.

 

Artificial intelligence (AI)

Image of icon for artificial intelligence
A general-purpose technology that enables and supports the application of many other technologies. A distinction is made between general AI and narrow AI. A general AI system is intended to be a system that can perform most activities that humans can do; according to experts, it is still far from being realised. A narrow AI system can perform just one or a few specific tasks; the AI systems that are deployed currently are narrow AI. Narrow AI uses machine learning and deep learning tools to extract information from an enormous amount of data and to generate new value based on models built with those data; it has many fields of application.

The EU High-level Expert Group on Artificial Intelligence defines AI as follows: 

'Artificial intelligence (AI) systems are software (and possibly also hardware) systems designed by humans that, given a complex goal, act in the physical or digital dimension by perceiving their environment through data acquisition, interpreting the collected structured or unstructured data, reasoning on the knowledge, or processing the information derived from this data and deciding the best action(s) to take to achieve the given goal. AI systems can either use symbolic rules or learn a numeric model, and they can also adapt their behaviour by analysing how the environment is affected by their previous actions.

As a scientific discipline, AI includes several approaches and techniques, such as machine learning (of which deep learning and reinforcement learning are specific examples), machine reasoning (which includes planning, scheduling, knowledge representation and reasoning, search, and optimization), and robotics (which includes control, perception, sensors and actuators, as well as the integration of all other techniques into cyber-physical systems).'

Reference documents:

Examples of application/use:

  • Used in a wide range of settings including the screening medical images, quality control and translation services.

 

Autonomous vehicle

Image of icon for autonomous vehicle
A vehicle that is able to sense and navigate its environment without human input. Examples include driverless cars, delivery drones and automated trucks.

 

Examples of application/use:

 

Blockchain 

Image of icon for blockchain
An application of distributed ledger technology, in which the ‘ledger’ comprises ‘blocks’ of transactions.

In a distributed ledger, information about a transaction is recorded onto the system permanently, and the information is simultaneously held by all the ‘participants’ (nodes) in the system, without the need for a central authority to certify that the transaction took place. This technology is the foundation of cryptocurrencies such as Bitcoin.

 

Examples of application/use:

 

Digitalisation

Image of icon for digitalisation
The broad transformation brought about by the widespread adoption of digital technologies. Within digitalisation, three broad categories of combined applications of digital technologies are differentiated: automation, digitisation and coordination by platforms. These are also called ‘vectors of change’.

 

 

Digitisation 

Image of icon for digitisation
The use of sensors and rendering devices to translate the physical production process, or parts of it, into digital information (and vice versa).

 

 

Electric vehicle

Image of icon for electric vehicle
A vehicle for which the main system of propulsion depends on electricity and not on fossil fuel. The vehicle relies on the storage of externally generated energy, generally in the form of rechargeable batteries. As of mid-2019, the main example is the battery-operated electric vehicle.

 

 

ICT-based mobile work

Image of icon for ICT-base mobile work
A work arrangement where an employee works on a regular or occasional basis outside their ‘main office’, be that the employer’s premises or a customised home office, using information and communication technologies (ICT). Work thus takes place wherever and at any time that suits the work activities, task, business schedule and lifestyle of the worker, not necessarily at a specific place but also ‘on the road’. Consequently, ICT-based mobile work takes place in ever-changing situations but with a need to collaborate with other workers or clients, hence the requirement to be connected to shared resources to achieve a joint goal.

 

 

Industrial biotechnology

Image of icon for industrial biotechnology
The use of biotechnological science in industrial processes. Modern biotechnology is based on the most recent scientific insights into the specific mechanisms of the biological processes within living organisms – for example, through systems genomics and metabolomics research (the large-scale study of small molecules). These insights are used to design processes in industry using yeasts, bacteria, fungi and enzymes (biological catalysts that improve reactions and that are relatively easy to obtain) to produce biomaterials and biofuels.

 

 

Internet of things (IoT)

Image of icon for internet of things
Networked sensors attached to outputs, inputs, components, materials or tools used in production. This encompasses electronic monitoring systems and wearable computing devices used for different purposes including monitoring work processes and employee performance and ultimately guiding management decision-making. 

Reference documents:

Examples of application/use:

  • In industrial manufacturing and agricultural processing, to monitor production processes
  • In utilities, for example, to monitor water quality
  • In logistics, to manage operations and the flow of products

For more examples, see the report Digitisation in the workplace.

 

Platform

Image of icon for platforms
An entity that organises digital networks to coordinate transactions in an algorithmic way. Three parties are involved in a digital platform: the online platform, the client and the user. Digital platforms aim to mediate the execution of specific tasks or the solving of specific problems.

 

 

 

Platform economy

Image of icon for platform economy
The economic activity generated by online platforms, including platforms matching the supply of and demand for paid labour (such as Uber), materials or capital; sales platforms (such as eBay); accommodation platforms (such as Airbnb); financial services platforms; and non-commercial platforms involving volunteering, networking, social media (such as LinkedIn) or any other form of unpaid transaction (such as Couchsurfing, for free accommodation).

 

 

 

Platform work

Image of icon for platform work
A form of employment and a business model that uses an online platform to enable organisations or individuals to access other organisations or individuals to solve problems or to provide services in exchange for payment, with strong reliance on an algorithm.

 

 

 

Virtual reality (VR) and augmented reality (AR)

Image of icon for virtual and augmented reality
Technology blending the digital and physical worlds by superimposing digital information over human perception of physical reality. While virtual reality (VR) is a computer-generated scenario that simulates a real-world experience, augmented reality (AR) combines real-world experience with computer-generated content.

Reference documents:

Examples of application/use:

  • AR glasses used in DHL supply-chain logistics to support order-picking instructions
  • In aviation, VR used extensively for training purposes
  • Augmented and mediated reality used in the Dutch National Police Corps for crime scene reconstructions
  • (More details on these and other examples can be found in the report Game-changing technologies: Transforming production and employment in Europe)

Disclaimer

When freely submitting your request, you are consenting Eurofound in handling your personal data to reply to you. Your request will be handled in accordance with the provisions of Regulation (EU) 2018/1725 of the European Parliament and of the Council of 23 October 2018 on the protection of natural persons with regard to the processing of personal data by the Union institutions, bodies, offices and agencies and on the free movement of such data. More information, please read the Data Protection Notice.