data mining
The methods of artificial intelligence, machine learning, statistics and databases used to extract content from a dataset.
digital
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Competences and skills
97 ESCO relationsEssential knowledge 18 competences
Occupation specific
0 competencesNo competences in this bucket.
Sector-specific
9 competencesdata models
The techniques and existing systems used for structuring data elements and showing relationships between them, as well as methods for interpreting the data structures and relationships.
digital
information categorisation
The process of classifying the information into categories and showing relationships between the data for some clearly defined purposes.
digital
information extraction
The techniques and methods used for eliciting and extracting information from unstructured or semi-structured digital documents and sources.
digital
online analytical processing
The online tools which analyse, aggregate and present multi-dimensional data enabling users to interactively and selectively extract and view data from specific points of view.
digital
query languages
The field of standardised computer languages for retrieval of information from a database and of documents containing the needed information.
digital
resource description framework query language
The query languages such as SPARQL which are used to retrieve and manipulate data stored in Resource Description Framework format (RDF).
digital
statistical modeling techniques
The approaches for employing statistical analysis to dataset within the data science field. It seeks to elaborate reality predictions through statistical models and explicit assumptions.
visual presentation techniques
The visual representation and interaction techniques, such as histograms, scatter plots, surface plots, tree maps and parallel coordinate plots, that can be used to present abstract numerical and non-numerical data, in order to reinforce the human understanding of this information.
digital
Cross-sector
9 competencesdata engineering
The process of developing and constructing systems for implementing data collection and analysis at large scale.
digital
data ethics
The subfield of ethics that assess whether data practices are considerable ethical. It assesses processes such as collecting, analysing and disseminating structured and unstructured data that might negatively impact the society.
data science
The field of study that deals with big amount of data using AI techniques such as machine learning algorithms to predict patterns and obtain useful information to make business decisions
digital
data visualisation software
A computer tool or application that creates a graphical and visual representation of data, allowing a better understanding and interpretation of complex data through visual elements such as maps, charts, infographics or graphs.
digital
empirical analysis
The evidence-based method that is used to analyse and interpret information with the aim of drawing conclusions about a specific issue.
mathematical modelling
The process of establishing a mathematical representation problem, such as equations, of a real-word to provide insights, discover new features about the problematic scenario, better understand the original problem or to make predictions about it.
quantitative analysis
The technique of employing statistical and mathematical modelling and measurement to represent a specific reality through numbers.
digital
scientific literature
The medium of informing the scientific community, including academic researchers, about the results of scientific research. It constitutes a permanent and cumulative collection of all the findings of scientific research in various fields and at any point in time.
statistics
The study of statistical theory, methods and practices such as collection, organisation, analysis, interpretation and presentation of data. It deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments in order to forecast and plan work-related activities.
Essential skills and competences 45 competences
Occupation specific
2 competencesbuild recommender systems
Construct recommendation systems based on large data sets using programming languages or computer tools to create a subclass of information filtering system that seeks to predict the rating or preference a user gives to an item.
digital
develop data processing applications
Create a customised software for processing data by selecting and using the appropriate computer programming language in order for an ICT system to produce demanded output based on expected input.
digital
Sector-specific
6 competencesdesign database scheme
Draft a database scheme by following the Relational Database Management System (RDBMS) rules in order to create a logically arranged group of objects such as tables, columns and processes.
digital
establish data processes
Use ICT tools to apply mathematical, algorithmic or other data manipulation processes in order to create information.
digital
manage data collection systems
Develop and manage methods and strategies used to maximise data quality and statistical efficiency in the collection of data, in order to ensure the gathered data are optimised for further processing.
digital
manage intellectual property rights
Deal with the private legal rights that protect the products of the intellect from unlawful infringement.
research
normalise data
Reduce data to their accurate core form (normal forms) in order to achieve such results as minimisation of dependency, elimination of redundancy, increase of consistency.
digital
operate open source software
Operate Open Source software, knowing the main Open Source models, licensing schemes, and the coding practices commonly adopted in the production of Open Source software.
digitalresearch
Cross-sector
37 competencesapply for research funding
Identify key relevant funding sources and prepare research grant application in order to obtain funds and grants. Write research proposals.
research
apply research ethics and scientific integrity principles in research activities
Apply fundamental ethical principles and legislation to scientific research, including issues of research integrity. Perform, review, or report research avoiding misconducts such as fabrication, falsification, and plagiarism.
research
collect ICT data
Gather data by designing and applying search and sampling methods.
digital
communicate with a non-scientific audience
Communicate about scientific findings to a non-scientific audience, including the general public. Tailor the communication of scientific concepts, debates, findings to the audience, using a variety of methods for different target groups, including visual presentations.
research
conduct research across disciplines
Work and use research findings and data across disciplinary and/or functional boundaries.
research
deliver visual presentation of data
Create visual representations of data such as charts or diagrams for easier understanding.
digital
demonstrate disciplinary expertise
Demonstrate deep knowledge and complex understanding of a specific research area, including responsible research, research ethics and scientific integrity principles, privacy and GDPR requirements, related to research activities within a specific discipline.
research
develop professional network with researchers and scientists
Develop alliances, contacts or partnerships, and exchange information with others. Foster integrated and open collaborations where different stakeholders co-create shared value research and innovations. Develop your personal profile or brand and make yourself visible and available in face-to-face and online networking environments.
research
disseminate results to the scientific community
Publicly disclose scientific results by any appropriate means, including conferences, workshops, colloquia and scientific publications.
research
draft scientific or academic papers and technical documentation
Draft and edit scientific, academic or technical texts on different subjects.
research
evaluate research activities
Review proposals, progress, impact and outcomes of peer researchers, including through open peer review.
research
execute analytical mathematical calculations
Apply mathematical methods and make use of calculation technologies in order to perform analyses and devise solutions to specific problems.
handle data samples
Collect and select a set of data from a population by a statistical or other defined procedure.
implement data quality processes
Apply quality analysis, validation and verification techniques on data to check data quality integrity.
digital
increase the impact of science on policy and society
Influence evidence-informed policy and decision making by providing scientific input to and maintaining professional relationships with policymakers and other stakeholders.
research
integrate gender dimension in research
Take into account in the whole research process the biological characteristics and the evolving social and cultural features of women and men (gender).
research
interact professionally in research and professional environments
Show consideration to others as well as collegiality. Listen, give and receive feedback and respond perceptively to others, also involving staff supervision and leadership in a professional setting.
research
interpret current data
Analyse data gathered from sources such as market data, scientific papers, customer requirements and questionnaires which are current and up-to-date in order to assess development and innovation in areas of expertise.
manage findable accessible interoperable and reusable data
Produce, describe, store, preserve and (re) use scientific data based on FAIR (Findable, Accessible, Interoperable, and Reusable) principles, making data as open as possible, and as closed as necessary.
digitalresearch
manage open publications
Be familiar with Open Publication strategies, with the use of information technology to support research, and with the development and management of CRIS (current research information systems) and institutional repositories. Provide licensing and copyright advice, use bibliometric indicators, and measure and report research impact.
digitalresearch
manage personal professional development
Take responsibility for lifelong learning and continuous professional development. Engage in learning to support and update professional competence. Identify priority areas for professional development based on reflection about own practice and through contact with peers and stakeholders. Pursue a cycle of self-improvement and develop credible career plans.
research
manage research data
Produce and analyse scientific data originating from qualitative and quantitative research methods. Store and maintain the data in research databases. Support the re-use of scientific data and be familiar with open data management principles.
digitalresearch
mentor individuals
Mentor individuals by providing emotional support, sharing experiences and giving advice to the individual to help them in their personal development, as well as adapting the support to the specific needs of the individual and heeding their requests and expectations.
research
perform data cleansing
Detect and correct corrupt records from data sets, ensure that the data become and remain structured according to guidelines.
digital
perform project management
Manage and plan various resources, such as human resources, budget, deadline, results, and quality necessary for a specific project, and monitor the project's progress in order to achieve a specific goal within a set time and budget.
research
perform scientific research
Gain, correct or improve knowledge about phenomena by using scientific methods and techniques, based on empirical or measurable observations.
research
promote open innovation in research
Apply techniques, models, methods and strategies which contribute to the promotion of steps towards innovation through collaboration with people and organizations outside the organisation.
research
promote the participation of citizens in scientific and research activities
Engage citizens in scientific and research activities and promote their contribution in terms of knowledge, time or resources invested.
research
promote the transfer of knowledge
Deploy broad awareness of processes of knowledge valorisation aimed to maximise the two–way flow of technology, intellectual property, expertise and capability between the research base and industry or the public sector.
research
publish academic research
Conduct academic research, in universities and research institutions, or on a personal account, publish it in books or academic journals with the aim of contributing to a field of expertise and achieving personal academic accreditation.
research
report analysis results
Produce research documents or give presentations to report the results of a conducted research and analysis project, indicating the analysis procedures and methods which led to the results, as well as potential interpretations of the results.
speak different languages
Master foreign languages to be able to communicate in one or more foreign languages.
research
synthesise information
Critically read, interpret, and summarise new and complex information from diverse sources.
research
think abstractly
Demonstrate the ability to use concepts in order to make and understand generalisations, and relate or connect them to other items, events, or experiences.
research
use data processing techniques
Gather, process and analyse relevant data and information, properly store and update data and represent figures and data using charts and statistical diagrams.
digital
use databases
Use software tools for managing and organising data in a structured environment which consists of attributes, tables and relationships in order to query and modify the stored data.
digital
write scientific publications
Present the hypothesis, findings, and conclusions of your scientific research in your field of expertise in a professional publication.
research
Optional knowledge 22 competences
Occupation specific
1 competencedigital curation
The field that deals with maintaining, preserving and adding value to digital research.
digital
Sector-specific
12 competencesbusiness analytics
The disciplines and technologies for solving business problems through employing quantitative methods such as data analysis and statistical models.
digital
computational biology
The interdisciplinary scientific field that focus on employing data analytics and theories to investigate biological systems obtained through experiments.
digital
data quality assessment
The process of revealing data issues using quality indicators, measures and metrics in order to plan data cleansing and data enrichment strategies according to data quality criteria.
digital
Hadoop
The open-source data storing, analysis and processing framework which consists mainly in the MapReduce and Hadoop distributed file system (HDFS) components and it is used to provide support for managing and analysing large datasets.
digital
healthcare analytics
The use of qualitative and quantitative methods to analyse patterns in healthcare data to the aim of improving healthcare administration, quality in patient care and diseases diagnosis.
LDAP
The computer language LDAP is a query language for retrieval of information from a database and of documents containing the needed information.
digital
LINQ
The computer language LINQ is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the software company Microsoft.
digital
MDX
The computer language MDX is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the software company Microsoft.
digital
N1QL
The computer language N1QL is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the software company Couchbase.
digital
SPARQL
The computer language SPARQL is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the international standards organisation World Wide Web Consortium.
digital
unstructured data
The information that is not arranged in a pre-defined manner or does not have a pre-defined data model and is difficult to understand and find patterns in without using techniques such as data mining.
digital
XQuery
The computer language XQuery is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the international standards organisation World Wide Web Consortium.
digital
Cross-sector
9 competencesbusiness intelligence
The tools used to transform large amounts of raw data into relevant and helpful business information.
digital
computer simulation
A programme run on a computer that represents dynamic responses of a system to explore a mathematical model behaviour, using a model of a real system, composed of mathematical equations.
digital
image recognition
A process designed to detect and identify a feature or object in an image or video. This process is used in medical imaging, security surveillance or defect detection, among other fields. Key technique for a wide range of applications such as automated driving, image classification, or visual inspection.
digital
marketing analytics
The set of processes for employing data to improve the effectiveness of marketing activities. It involves analysing metrics such as the Return on Investment (ROI) for identify opportunities of improvement.
digital
multidisciplinary research
The research technique where a common issue is investigated using approaches from different disciplines with the aim of finding a comprehensive solution to it.
research design
The set of methods and techniques of research that are used to conduct a study. It includes practical steps in research such as purpose statement, data collection, methodology, and data analysis.
scientific computing
The interdisciplinary field between computer science, mathematics and engineering. It concerns the employment of technical approaches and theoretical frameworks, and the use of computers, to address issues in science and engineering.
digital
social network analysis
The research method that is mainly explored in sociology and communication science and focuses on the analysis of the relations between individuals and among organisations and states.
state estimation
The process of fusing input data measurements and a mathematical model to determine the internal state of an energy system
Optional skills and competences 12 competences
Occupation specific
0 competencesNo competences in this bucket.
Sector-specific
8 competencescreate data models
Use specific techniques and methodologies to analyse the data requirements of an organisation's business processes in order to create models for these data, such as conceptual, logical and physical models. These models have a specific structure and format.
digital
define data quality criteria
Specify the criteria by which data quality is measured for business purposes, such as inconsistencies, incompleteness, usability for purpose and accuracy.
design database in the cloud
Apply design principles for an adaptive, elastic, automated, loosely coupled databases making use of cloud infrastructure. Aim to remove any single point of failure through distributed database design.
digital
integrate ICT data
Combine data from sources to provide unified view of the set of these data.
digital
manage data
Administer all types of data resources through their lifecycle by performing data profiling, parsing, standardisation, identity resolution, cleansing, enhancement and auditing. Ensure the data is fit for purpose, using specialised ICT tools to fulfil the data quality criteria.
digital
manage ICT data architecture
Oversee regulations and use ICT techniques to define the information systems architecture and to control data gathering, storing, consolidation, arrangement and usage in an organisation.
digital
manage ICT data classification
Oversee the classification system an organisation uses to organise its data. Assign an owner to each data concept or bulk of concepts and determine the value of each item of data.
digital
perform data mining
Explore large datasets to reveal patterns using statistics, database systems or artificial intelligence and present the information in a comprehensible way.
digital
- Scope note
- Includes activities on big data.
Cross-sector
4 competencesapply blended learning
Be familiar with blended learning tools by combining traditional face-to-face and online learning, using digital tools, online technologies, and e-learning methods.
digitalresearch
make data-driven decisions
Collect data such as Key Performance Indicators (KPIs) for an organisation and use the information to formulate actions and strategies.
teach in academic or vocational contexts
Instruct students in the theory and practice of academic or vocational subjects, transferring the content of own and others' research activities.
research
use spreadsheets software
Use software tools to create and edit tabular data to carry out mathematical calculations, organise data and information, create diagrams based on data and to retrieve them.
digital