Embedding formal knowledge models in active documents

1999 ◽  
Vol 42 (1) ◽  
pp. 57-64 ◽  
Author(s):  
Brian R. Gaines ◽  
Mildred L. G. Shaw
Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 600
Author(s):  
Edrisi Muñoz ◽  
Elisabet Capon-Garcia ◽  
Enrique Martinez Muñoz ◽  
Luis Puigjaner

Process, manufacturing, and service industries currently face a large number of non-trivial challenges ranging from product conception, going through design, development, commercialization, and delivering in a customized market’s environment. Thus, industries can benefit by integrating new technologies in their day-by-day tasks gaining profitability. This work presents a model for enterprise process development activities called the wide intelligent management architecture model to integrate new technologies for services, processes, and manufacturing companies who strive to find the most efficient way towards enterprise and process intelligence. The model comprises and structures three critical systems: process system, knowledge system, and transactional system. As a result, analytical tools belonging to process activities and transactional data system are guided by a systematic development framework consolidated with formal knowledge models. Thus, the model improves the interaction among processes lifecycle, analytical models, transactional system, and knowledge. Finally, a case study is presented where an acrylic fiber production plant applies the proposed model, demonstrating how the three models described in the methodology work together to reach the desired technology application life cycle assessment systematically. Results allow us to conclude that the interaction between the semantics of formal knowledge models and the processes-transactional system development framework facilitates and simplifies new technology implementation along with enterprise development activities.


2020 ◽  
pp. 93-102
Author(s):  
Fabrizio d'Aniello

The pre-eminent motivation behind this contribution lies in the intention to offer students of three-year degree course in education and training sciences and master's degree in pedagogical sciences of the University of Macerata a further support than those already existing, aimed at expanding the educational meaningfulness of the internship experience. The main criticality of such experience is connected with the difficulty in translating knowledge, models, ideas into appropriate activities. This notably refers to the conceptual and educational core of the sense of initiative and entrepreneurship and, consistently, to the skill to act. Therefore, after a deepening of the sense of initiative and entrepreneurship, followed by related pedagogical reflections based on the capability approach, the paper presents an operative proposal aimed at increasing young people's possibilities of action and supporting their personal and professional growth. With regard to this training proposal, the theoretical and methodological framework refers to the third generation cultural historical activity theory and to the tool of the boundary crossing laboratory, variant of the change laboratory


1989 ◽  
Vol 29 (1) ◽  
pp. 1-9
Author(s):  
Juan B. Castellanos Peñuela ◽  
Rafael Gonzalo Molina ◽  
Juan Pazos Sierra ◽  
Juan Rios Carrión

2003 ◽  
Vol 1 (1) ◽  
pp. 081-110 ◽  
Author(s):  
Gully A P C Burns ◽  
Arshad M Khan ◽  
Shahram Ghandeharizadeh ◽  
Mark A O'Neill ◽  
Yi-Shin Chen

Author(s):  
Man Tianxing ◽  
Nataly Zhukova ◽  
Alexander Vodyaho ◽  
Tin Tun Aung

Extracting knowledge from data streams received from observed objects through data mining is required in various domains. However, there is a lack of any kind of guidance on which techniques can or should be used in which contexts. Meta mining technology can help build processes of data processing based on knowledge models taking into account the specific features of the objects. This paper proposes a meta mining ontology framework that allows selecting algorithms for solving specific data mining tasks and build suitable processes. The proposed ontology is constructed using existing ontologies and is extended with an ontology of data characteristics and task requirements. Different from the existing ontologies, the proposed ontology describes the overall data mining process, used to build data processing processes in various domains, and has low computational complexity compared to others. The authors developed an ontology merging method and a sub-ontology extraction method, which are implemented based on OWL API via extracting and integrating the relevant axioms.


2021 ◽  
Author(s):  
David Guerra-Zubiaga ◽  
Basma Siddiqui ◽  
Navid Nasajpour-Esfahani ◽  
Kevin Kamperman

2021 ◽  
Author(s):  
Yiqing Zhao ◽  
Matthew Brush ◽  
Chen Wang ◽  
Hongfang Liu ◽  
Robert R Freimuth

BACKGROUND Despite the increasing evidence of utility of genomic medicine in clinical practice, systematically integrating genomic medicine information and knowledge into clinical systems with a high-level of consistency, scalability, and computability remains challenging. A comprehensive terminology is required for relevant concepts and the associated knowledge model for representing relationships. OBJECTIVE Our study aims to propose a drug response phenotype terminology to represent relationships between genetic variants and drugs in existing knowledge models. METHODS In this study, we leveraged PharmGKB, a comprehensive pharmacogenomics (PGx) knowledgebase, to formulate a terminology for drug response phenotypes that can represent relationships between genetic mutations and treatments. We evaluated coverage of the terminology through manual review of a randomly selected subset of 200 sentences extracted from genetic reports that contained concepts for “Genes and Gene Products” and “Treatments”. RESULTS Results showed that our proposed drug response phenotype terminology could cover 96% of the drug response phenotypes in genetic reports. Among 18,653 sentences that contained both “Genes and Gene Products” and “Treatments”, 3,011 sentences were able to be mapped to a drug response phenotype in our proposed terminology, among which the most discussed drug response phenotypes were response (994), sensitivity (829), and survival (332). In addition, we were able to re-analyze genetic report context incorporating the proposed terminology and enrich our previously proposed PGx knowledge model to reveal relationships between genetic mutations and treatments. CONCLUSIONS In conclusion, we proposed a drug response phenotype terminology that enhanced structured knowledge representation of genomic medicine.


2007 ◽  
Vol 26 (3) ◽  
pp. 39 ◽  
Author(s):  
Javier Lacasta ◽  
Javier Nogueras-Iso ◽  
Francisco Javier López-Pellicer ◽  
Pedro Rafail Muro-Medrano ◽  
Francisco Javier Zarazaga-Soria

Knowledge organization systems denotes formally represented knowledge that is used within the context of digital libraries to improve data sharing and information retrieval. To increase their use, and to reuse them when possible, it is vital to manage them adequately and to provide them in a standard interchange format. Simple knowledge organization systems (SKOS) seem to be the most promising representation for the type of knowledge models used in digital libraries, but there is a lack of tools that are able to properly manage it. This work presents a tool that fills this gap, facilitating their use in different environments and using SKOS as an interchange format.


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