“…Then this wide knowledge has to be of a certain kind, a kind that applies to the many and varied problems of life. A person may have encyclopedic knowledge of the facts and figures relating to the countries of the world, but that knowledge, of itself, will not make that person wise” (Fricke, 2019).…”
Section: Storytelling and Data Information Knowledge And Wisdommentioning
Most information science (IS) definitions of information center individual rather than collective meaning‐making. Because stories are constituted through narrative experience, and audiences are partly constitutive of the stories told to and with them, storytelling offers a framework for researching collective experiences of information. Stories are simultaneously empirical and socially constructed, bridging a key epistemological divide in IS. Storytelling as paradigm shift is explored and demonstrated in three sections that (a) define story and storytelling, (b) describe how story and storytelling can extend the data, information, knowledge, and wisdom (DIKW) pyramid, and (c) revise DIKW as a new storytelling S‐DIKW framework. Future IS storytelling research should account for story and the dynamics of storytelling not merely as a subset of information or of information behavior, but as a fundamental information form.
“…Then this wide knowledge has to be of a certain kind, a kind that applies to the many and varied problems of life. A person may have encyclopedic knowledge of the facts and figures relating to the countries of the world, but that knowledge, of itself, will not make that person wise” (Fricke, 2019).…”
Section: Storytelling and Data Information Knowledge And Wisdommentioning
Most information science (IS) definitions of information center individual rather than collective meaning‐making. Because stories are constituted through narrative experience, and audiences are partly constitutive of the stories told to and with them, storytelling offers a framework for researching collective experiences of information. Stories are simultaneously empirical and socially constructed, bridging a key epistemological divide in IS. Storytelling as paradigm shift is explored and demonstrated in three sections that (a) define story and storytelling, (b) describe how story and storytelling can extend the data, information, knowledge, and wisdom (DIKW) pyramid, and (c) revise DIKW as a new storytelling S‐DIKW framework. Future IS storytelling research should account for story and the dynamics of storytelling not merely as a subset of information or of information behavior, but as a fundamental information form.
“…When Data is organized and structured, becoming meaningful and relevant, it becomes Information (Rowley 2007), i.e., Information is contextualized Data. Some authors refer to Information as "weak-knowledge" (Frické 2019). Knowledge is combined information sets analyzed by a human through her/his understanding, experiences, skills, and values (Rowley 2007), i.e., Knowledge is combined and interpreted Information.…”
Section: The Design Process Knowledge and Artifactsmentioning
confidence: 99%
“…Third, the "social model" describes the interactions between individuals and groups that enable the transformation of knowledge created during the process that leads to organizational learning. This model is based on the transformation of tacit knowledge (i.e., the inexpressible personal knowledge) and explicit knowledge (i.e., the expressible and recordable knowledge documented as artifacts) (Frické 2019). According to the SECI model proposed by Nonaka and Takeuchi (1995), organization learning takes place by the combination of the processes of Socialization (tacit to tacit knowledge), Externalization (tacit to explicit knowledge), Combination (explicit to explicit knowledge), and Internalization (explicit to tacit knowledge).…”
Section: The Design Process Knowledge and Artifactsmentioning
Designing Product-Service Systems (PSS) is associated with multiple problems and challenges, usually derived from its multidisciplinarity and partially intangible nature. One particular issue is the high likelihood of ignoring the creation of relevant information regarding one or more PSS elements during the early design phases. Proceeding to later stages (e.g., detailed design) without generating the required information regarding all PSS elements and their relationships may lead to rework and lack of integration. Dealing with this problem requires adequate planning and evaluation of the artifacts (such as documents and models) created in the initial design phases. As a fundamental theoretical basis to support the creation of solutions that may help project managers dealing with this challenge, this paper presents a concept map to structure the concepts that compose artifacts resulting from the initial stages of PSS design and how those concepts interrelate. This concept map aims to structure which classes of information should be defined in the early phases of the design process before proceeding to a detailed design. The concept map was created by extracting concepts and relationships proposed in classifications, taxonomies, ontologies, meta-models, and concept maps in the PSS and servitization fields. Those documents were identified through a comprehensive systematic literature review. The resulting concept map was verified for completeness against formal documentation of two retrospective PSS design projects. The final proposed concept map is composed of 143 concepts interconnected through 278 relationships. In its current format, the concept map may be used as a checklist to support project managers in planning and evaluating early phases of PSS design based on information completeness. Researchers may also employ it to deploy ontologies, approach further knowledge and information-related challenges in PSS design, or structure PSS-related model-based systems engineering approaches. In future research, this concept map shall be deployed in a meta-model based on artifacts commonly used in PSS design, structuring a computational tool to allow and support practical application on planning and evaluating PSS design projects.
“…This transformation happens when the data is converted in knowledge. This series of transformations are depicted in the "knowledge pyramid" defined in [11].…”
Nowadays, companies and official bodies are using the data as a principal asset to take strategic decision. The advances in big data processing, storage and analysis techniques have allowed to manage the continuous increase in the volume of data. This increase in the volume of data together with its high variability and the large number of sources lead to a constant growing of the complexity of the data management environment. Data governance is the key for simplifying that complexity: it is the element that controls the decision making and responsibilities for all the processes related to data management. This paper discusses an approach to data governance based on ontological reasoning to reduce data management complexity. The proposed data governance system is built over an autonomous system based on distributed components. It uses semantic techniques and automatic ontology-based reasoning, with the different component using a Shared Knowledge Plane to interact. Its fundamental piece is an ontology that represents all the data management processes included in data governance. A prototype of such a system has been implemented and tested for Telefonica´s global video service. The results obtained show the feasibility of using this type of technology to reduce the complexity of managing big data environments.INDEX TERMS Big data, data governance, knowledge-based management, ontologies, reasoning, OWL, SWRL.
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