scholarly journals Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases

2021 ◽  
Vol 10 (2-4) ◽  
pp. 108-490
Author(s):  
Gerhard Weikum ◽  
Xin Luna Dong ◽  
Simon Razniewski ◽  
Fabian Suchanek
Author(s):  
Kirsimarja Blomqvist

Technology partnerships are seen as a key element both in knowledge creation for technological development itself and in leveraging the value of technological knowledge (Bidault & Cummings, 1994; Teece, 1987; Ford, 1998). Complementary knowledge is generally regarded as a source for competitiveness (Doz & Hamel, 1998; Powell, 1998; Nahapiet & Ghoshal, 2000). Potentially, the focus on core competencies enables relatively stronger competitiveness (cumulative learning, focused use of critical resources) and ability to gain synergistic benefits and scale by leveraging different knowledge bases and networks (Miles, 2000; Blomqvist, 2002).


2003 ◽  
Vol 24 (3) ◽  
pp. 5-7 ◽  
Author(s):  
Patrick Marren

Discusses the economy and knowledge management via a knowledge bases and looks at where this knowledge base is today. States knowledge is a human being’s rightful certainty of what is actually the case, but does not help directly with knowledge on the job. Uses an example of a knowledge creation of a substitute, robot‐like creature called a “Golem” with cautionary, tragic results, to show what could happen in business organizations.


Author(s):  
Melissa Adler ◽  
Joseph T. Tennis ◽  
Stas̆a Milojević ◽  
Seth van Hooland ◽  
Corinne Rogers ◽  
...  

2017 ◽  
Vol 46-47 ◽  
pp. 2-13 ◽  
Author(s):  
Raphaël Troncy ◽  
Giuseppe Rizzo ◽  
Anthony Jameson ◽  
Oscar Corcho ◽  
Julien Plu ◽  
...  

2020 ◽  
Author(s):  
Chaitra Sarathy ◽  
Marian Breuer ◽  
Martina Kutmon ◽  
Michiel E. Adriaens ◽  
Chris T. Evelo ◽  
...  

Being a comprehensive knowledge bases of cellular metabolism, Genome-scale metabolic models (GEMs) serve as mathematical tools for studying cellular flux states in various or-ganisms. However, analysis of large-scale GEMs, such as human models, still presents considerable challenges with respect to objective selection and reaction flux constraints. In this study, we introduce a model-based method, ComMet (Comparison of Metabolic states), for comprehensive analysis of large metabolic flux spaces and comparison of various metabolic states. ComMet allows (a) an in-depth characterisation of flux states achievable by GEMs, (b) comparison of flux spaces from several conditions of interest, (c) identification of metabolically distinct network modules and (d) visualisation of network modules as reaction and metabolic map. As a proof-of-principle, we employed ComMet to extract the biochemical differences in the human adipocyte network (iAdipocytes1809) arising due to unlimited/blocked uptake of branched-chain amino acids. Our study opens avenues for exploring several metabolic condi-tions of interest in both microbe and human models. ComMet is open-source and is available at https://github.com/macsbio/commet.


2012 ◽  
Vol 18 (4) ◽  
pp. 495-504 ◽  
Author(s):  
Saumyendu Ghosh ◽  
Lenis Amaya ◽  
Mirosław J. Skibniewski

Projects undertaken in the project-based industry are characterized by multiple stakeholders, uncertainty, and complexity due to the unique nature of each project. These differences also extend to knowledge movement from one project to another. Increased knowledge creation resulting from project implementation is expected to lead to numerous benefits. These benefits encompass reusability of lessons learned, as well as knowledge of strategic, operational, organizational, and managerial aspects of the firm. By adopting a unified knowledge creation framework, firms seek tangible and intangible benefits such as cost reduction, improved productivity, enhanced efficiency, and business growth. A case study was used to identify problem areas of knowledge creation and align corporate and project objectives. Incorporating a comprehensive knowledge creation plan in the organizational memory infrastructure can be a significant stride toward improving overall project management efficiency and increasing the organization's productivity and profitability in the industry. This stream of research will allow researchers to further refine knowledge creation success models. The paper will also draw practitioners’ attention to areas where investment is needed to improve the knowledge governance process.


2001 ◽  
Vol 05 (02) ◽  
pp. 213-237 ◽  
Author(s):  
PETER MASKELL

The established fact that knowledge in society is always distributed and dispersed can be given a dynamic interpretation when perceived as the outcome of an ongoing deepening of the division of labour as suggested by Adam Smith. Individuals specialising on performing certain tasks are motivated to find solutions and notice peculiarities otherwise overlooked. Thus, this gives rise to the suspicion that the process of innovation and learning is fuelled by the development of distinct bodies of knowledge developed in independent organisations pursuing objectives of competitiveness. Specialisation and outsourcing, etc., aim at freeing managerial and other resources within the firm to be relocated in developing core capabilities or competencies and in enhancing the internal learning processes. The boundaries of the firm thus impact directly on the (possible) level of learning in the economy. However, developing distinct bodies of knowledge increases the cognitive distance that firms have to overcome when engaged in inter-organisational learning. This must imply that interorganisational learning is subject to thresholds, before the dispersed knowledge bases of firms have grown sufficiently apart for interacting to imply learning; and ceilings, after which the cognitive distance becomes too great for firms to bridge, and where learning, consequentially, will cease. The paper argues that geographical clusters constitute an unplanned and organically developed mechanism for reducing cognitive distance between firms and thereby the cost of knowledge transfer and utilisation, while at the same time maintaining the specialisation within and between firms necessary for creating new knowledge.


Author(s):  
Raphael Troncy ◽  
Giuseppe Rizzo ◽  
Anthony Jameson ◽  
Oscar Corcho ◽  
Julien Plu ◽  
...  

2021 ◽  
Author(s):  
Yasser MOHSENI BEHBAHANI ◽  
Paul SAIGHI ◽  
Flavia CORSI ◽  
Elodie LAINE ◽  
Alessandra CARBONE

The complexity underlying protein-protein interaction (PPI) networks calls for the development of comprehensive knowledge bases organizing PPI-related data. The constant growth and high reliability of structural data make them a suitable source of evidence for the determination of PPI. We present LEVELNET, a fully-automated and scalable environment designed to integrate, explore, and infer protein interactions and non-interactions based on physical contacts and other PPI sources, including user-defined annotations. LEVELNET helps to break down the complexity of PPI networks by representing them as multi-layered graphs and allowing the selection of subnetworks and their direct comparison. LEVELNET proposes an interactive visualisation based on a user-friendly web interface. LEVELNET applications are multiple. It allows to explore PPIs of biological processes, identify co-localised partners, assess PPI predictions from computational or experimental sources, unravel cross-interactions, show and compare multiple PPI sources, and help creating PPI benchmarks with specific properties. Availability: LEVELNET is freely available to the community at http://www.lcqb.upmc.fr/levelnet/


Author(s):  
Paul Witherell ◽  
Sundar Krishnamurty ◽  
Ian Grosse ◽  
Jack Wileden

The Semantic Web, especially in relation to ontologies, provides a structured, formal framework for knowledge interoperability. This trait has been exploited by both the biomedical community in development of the Human Gene Ontology [1] and also by geographers in development of geospatial ontologies [2]. Using semantic relatedness techniques, researchers from both communities have been able to develop and integrate comprehensive knowledge bases. Beyond knowledge integration, semantic relatedness techniques have also been able to provide each community with a unique insight into relationships between concepts in their respective domains. In the engineering community, semantic relatedness techniques promise to provide similar insight into product development processes. This paper explores the application of semantic relatedness techniques to ontologies as a means towards improved knowledge management in product development processes. Several different semantic relatedness techniques are reviewed, including a recently developed meronomic technique specific to domain ontologies. Three of these techniques are adopted to create a semantic relatedness measure specifically designed to identify and rank underlying relationships that exist between aspects of the product development process. Four separate case studies are then presented to evaluate the relative accuracy of the developed algorithm and then determine its effectiveness in exposing underlying relationships.


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