Download Journal on Data Semantics XIII by Victoria Nebot, Rafael Berlanga, Juan Manuel Pérez (auth.), PDF

By Victoria Nebot, Rafael Berlanga, Juan Manuel Pérez (auth.), Stefano Spaccapietra, Esteban Zimányi, Il-Yeol Song (eds.)

The LNCS magazine on information Semantics is dedicated to the presentation of extraordinary paintings that, in a single manner or one other, addresses examine and improvement on concerns with regards to info semantics. The scope of the magazine levels from theories aiding the formal definition of semantic content material to cutting edge domain-specific purposes of semantic wisdom. The magazine addresses researchers and complicated practitioners engaged on the semantic net, interoperability, cellular details prone, facts warehousing, wisdom illustration and reasoning, conceptual database modeling, ontologies, and synthetic intelligence.

Volume XIII constitutes a unique factor on semantic information warehouses. The papers during this quantity tackle a number of subject matters inside this rather new area, supplying diverse insights into the a number of merits that may be received via envisioning info warehouses from a semantic point of view. those papers broach many new principles to be addressed in destiny paintings.

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Here, we can conclude that both concepts are related somehow with Connective_ and_Soft_Tissue. Similarly, we can find some dependency between RA and blood sample biomarkers as RA is an autoimmune disease that mainly affect to macrophage cells in the blood. Indeed, the original definition of biomarker is that it provides clues to diagnose a disease, thus the strong dependency between both concepts. 5 Phase 4: OLAP-Based Analysis Before building the target OLAP-based cube, the MIO must be properly populated with the instances from the Semantic Data Warehouse that satisfy both the MIO and the set of specific roll-up relationships between them.

For example, the users can easily state facts and dimensions of analysis by selecting the relevant concepts from the ontologies. The methodology’s underlying multidimensional model is very simple, only facts, measures, dimensions, categories and roll-up relationships need to be identified. This will allow us to implement the model in almost any existing multidimensional database by performing the proper transformations. Regarding the scalability of the approach, we are able to manage large-sized ontologies by selecting fragments representing semantically complete knowledge modules.

Finally, we consider that addressing the temporal aspects of the semantic annotations, and the incremental consistency checking and reasoning with our MIObased approach are also very attractive challenges. In the future work we plan to carry out a deeper study of alternative implementations of SDWs. The main drawbacks of the current implementation include that the data may become outdated due to sources updates and that the extraction and validation process takes a long time to perform. A problematic issue which is particular to SDWs is that especially external data may have such a bad quality that the validation checks may disallow their integration in the materialized data warehouse, even if some parts of the data have sufficient quality.

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