Data, Knowledge and Information Engineering

§ 6.0

Branches

الفروع

Code	Branch	Scope
6.1	Data Lifecycle	The stages of data from collection, cleaning and labelling to storage, splitting, archiving and disposal, and the data-engineering practices needed to train and evaluate models
6.2	Knowledge Graphs and Ontologies	Representing knowledge in structured forms: knowledge graphs, ontologies and semantic schemas, and their construction, extraction from text and maintenance
6.3	Synthetic Data and Simulation	Generating synthetic data for training and testing, simulation and its environments, and the benefits and risks of this approach such as model collapse and the reproduction of bias
6.4	Quality, Documentation and Provenance	Data quality criteria, documentation tools such as datasheets, tracking of provenance and lineage, and checking datasets for bias
6.5	Privacy, Federated Learning and Anonymization	Technical protection of personal data: differential privacy, federated learning, anonymization, confidential computing, and the risks of extracting data from models
6.6	Data Rights, Text and Data Mining, and Copyright	The legal frameworks of data: copyright, text and data mining, licences, fair-use exceptions, ownership of outputs and the claims of content owners
6.7	Interoperability and Shared Resources	Agreements for exchanging data and knowledge between systems: exchange formats, persistent identifiers, shared vocabularies, open resource repositories, and principles of discoverability and reuse