| Popis: |
The product lifecycle spans from idea generation, design, manufacturing, and service to disposal. During all these phases, engineers use their knowledge to fulll their tasks. If engineers retire or leave a company, their embodied knowledge also resigns. To circumvent such loss of important company's intellectual property, and to enable traceability and reuse of product data in the future, the engineer's knowledge is captured as metadata and then used as annotation for product lifecycle data. Since such annotated product data models represent meaning in conformance with ontologies, product data can easier be explored, understood and reused by future product lifecycle actors. For business, contractual, and legal reasons, these semantically enriched models are ingested into OAIS (Open Archival Information System) based archives for later reuse. Notably, it is not uncommon for a product service provider to operate products for several decades; even after the engineers whose embodied knowledge supports their operation retire or leave the company. This product longevity and volatile knowledge, alongside rapid technological innovations and evolving ontologies result in diculties of reusing archived product data in the long-term. Especially, domain ontologies must re ect changes in real world phenomena which they describe. Therefore, special preservation processes are required to prevent semantic obsolescence of archived product data due to changes in domain conceptualization and to keep the archived product data and metadata interpretable. While preservation of the data is concerned with product data normalization, validation and le format migration, the preservation processes for metadata are of a dierent nature given that referenced ontologies evolve independently from the products they describe. Although widely referenced, the OAIS reference model unfortunately does not observe ontology evolution or metadata preservation in any depth. This thesis therefore aims to introduce dedicated metadata harmonization functionality into OAIS archives, based on operational ontology update processing which together build a semantic digital archive system architecture that enables to preserve captured metadata under knowledge evolution. |
