Glossary of digitalisation and research data management
| Definition | Data describing a datum or a data set. Ideally as structured, standardised set of information provided directly with the data it describes. |
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| Remarks | Metadata can be stored as part of the file itself, as for image data, or separately, as for data repositories organised based on metadata information. Metadata is an important prerequisite to fulfil the FAIR principles for data |
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| QR code | Camera-readable information in a standardised form. A QR code encodes a small amount of digital information and is usually used to encode the link to a website or similar resource. |
| With QR codes, the process for customers to access information provided by a calibration laboratory can be eased. Since the QR code is provided directly with the device, digital information is linked to the physical device. |
| Definition | Semantic modelling of terms and their relation in a way that can be interpreted by software tools. |
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| Remarks | Ontologies are a tool to create interoperability for data sets of different sources, by using them to formulate the metadata in a semantic modelling language. That is, ontologies link annotations between different applications and domains. |
| Definition | Information provided such that it can be accessed (read) by a machine (software) autonomously (without human interaction. |
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| Remarks | Machine readable metadata is an important prerequisite for making data FAIR. |
| Definition | Information provided such that it can be interpreted by a machine (software) autonomously (without human interaction. |
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| Remarks | Machine actionable data is usually structured in a more granular way than machine readable data. Ontologies or other semantic information are usually used to make information machine actionable, because they encode human knowledge in a structured form. |
| Definition | Documented interface that can be accessed by a software as a means to share information between digital systems. |
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| Definition | Set of general rules and procedures for making data findable, accessible, interoperable and reusable. |
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| Remarks | The FAIR principles originate from the scientific community and a part of the international efforts to make research reproducible. However, the FAIR principles can also be applied to internal data management and to the provision of digital services. |
| Definition | Machine actionable digital format of a calibration certificate. |
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| Definition | Machine actionable digital format encoding the information about a requested calibration. |
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| Remarks | Related to a DCR is the DCA – the digital calibration answer. It encodes the DCC for the calibration together with other order-related information from the laboratory to the customer. DCR, DCA and DCC should ideally be based on very similar schema elements to avoid translation errors. |
| Definition | Electronic / digital record containing key information about a physical asset (product, device, …. |
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| Remarks | DPPs are becoming mandatory for a wide range (almost all) product categories in the European Union over the next couple of years. International uptake and standardisation of DPPs are, for instance, be supported by UNECE. The major motivation for DPPs is to enable verifiable statements about origin of materials, product properties and information for recycling and reuse in a digital way. |
| Definition | Digital way to interact with customers. |
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| Remarks | Access to the customer portal may be provided also via a QR code leading the customer directly to the corresponding part of the website. with information about the measuring instrument. BEV in Austria and the legal metrology organisation of Singapore already use QR codes. for their customers and end users to provide access to measuring device information and access to services such as ordering a re-verification. |
| Definition | Methodology to train algorithms / model parameters based on training data. |
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| Remarks | Machine learning typically uses models that do not contain explicit physical / domain knowledge. That is, the domain knowledge has to be contained in the data used for training (model parameter identification). |
| Definition | Machine learning using artificial neural networks with many highly interconnected layers. Training (i.e., parameter identification) for a deep neural network is called deep learning. |
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| Remarks | Many AI systems today use deep neural networks as model architecture with specialised layers and structure. For example, convolutional neural networks use elements from image processing (e.g., edge detection) as part of the neural network. |
| Definition | Describing the process of implementing automated end-to-end digital workflows, providing machine actionable measurement data and reports, and software-based autonomous processes and services in metrology. |
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| Definition | Process of creating a software to perform a predefined task in a reproducible way. |
| Further details | For high quality software, the development process should contain especially the following elements:
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| Remarks | MATHMET developed a software quality assurance framework oriented at software used in measurement data analysis and modelling. Several ISO standards exist for software development practices. Software transparency ensures reusability of software even when the developer team changes, and it creates trust and confidence in the software being developed. |
| Definition | Quality infrastructure (metrology, accreditation, conformity assessment, standardisation, market surveillance) with data, processes and information being digitally transformed. |
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| Remarks | The aim of the digital QI is to make processes faster, more efficient and easier to use for everyone. It requires inputs, processes and outcomes to be digital and interoperable. A digital QI adheres to the FAIR principles and provides information and services in a machine actionable way. |
| Definition | System of data bases and services interconnected by means of shared access and metadata repositories. |
| Further details | The data in a data space can be stored, accessed and shared easily based on predefined rules and access rights. Architecture models for data spaces usually also contain elements such as metadata brokers, vocabulary services, and identity providers, to ease automated data and service access and improve interoperability. |
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| Remarks | The European Commission aims for a „Common European Dataspace“ between industries, governmental and non-governmental services and data sources. Initiatives such as GAIA-X and International Data Spaces are coordinating about 200 data spaces in Europe. A standardisation request from the EC to CEN/CENELEC is in preparation to harmonise technologies and requirements for data spaces in Europe. International standardisation for data spaces has been initiated at ISO. |