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![The opening page of Google’s Knowledge Graph [30]](profile/Gyuri-Lajos/publication/280235986/figure/fig1/AS:284465789194245@1444833337761/The-opening-page-of-Googles-Knowledge-Graph-30.png)
The opening page of Google’s Knowledge Graph [30]
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![Figure 5: The opening page of Google’s Knowledge Graph [30]](profile/Gyuri-Lajos/publication/280235986/figure/fig1/AS:284465789194245@1444833337761/The-opening-page-of-Googles-Knowledge-Graph-30_Q320.jpg)
Computer enhanced technology gives us access to collective knowledge that needs to be contextualized, personalized, and reorganized. This is a major task for next generation learners and knowledge workers for whom searching, gathering, digesting, producing, and presenting information makes sense in personal problem solving contexts. Personal ways o...
Citations
... (Cf. [1][2][3][4][5]) Using existing capabilities we are well on the way to completing within WikiNizeR a full "Intent Graphical" Model of all its capabilities. This model is set out as a Capability Graph as an example of a personal knowledge graph that can be accessed in WikiNizeR. ...
... The entire user interface therefore becomes but a specific dynamic visualization of use case dependent trails within the capability graph. In the second stage of bootstrapping the system will become user extensible, and co-evolvable through meta-design, [5,7] turning it into a Knowledge Augmentation Engine. ...
for an update on where this research is heading todya please check out
https://www.researchgate.net/publication/334126329_Weaving_a_Decentralized_Semantic_Web_of_Personal_Knowledge
WikiNizer™ Research (WikiNizeR) is a visual Wiki-like knowledge orgaNizer which constructs Personal Knowledge Graphs. By enabling us to visualize "meta" levels of reflection, WikiNizeR facilitates our sense making and problem solving. Using Freebase as a linked data source it harvests and contextualizes semantically structured information, empowering us to curate a private Knowledge Graph of Things, which a view also to enhancing collaborative knowledge work. Its users integrate open web data within the content driven graph architectures of their personal learning environments. It enables us to elaborate upon the emergent dynamic graphs which articulate the typed connections that exist between 'Things' of interest, facilitating the emergence of novel concepts in the associated complexes of content which are organized into node based structures. It supports a connectivist learning model; and as a "self-curating" semantic knowledge management tool it can be used in problem and project based learning to explore resources and conceptual relationships, helping us to define learning paths and workflows, or design meta-level didactic object structures and activities. It is a tool which helps us track meaning construction in a situated, intent dependent and dynamic manner. It is a holistic solution which integrates web research, linked data, annotation, note-taking and knowledge organization into a Lifelong Personal Digital Archive of "born reproducible", ab initio re-purposable, and re-enactable, Research Objects. Track: Open Track
https://www.linkedin.com/feed/update/urn:li:activity:6560853812054237184
... In an earlier paper we spelt out our vision of what a " Next generation concept organization tool " should accomplish. (Benedek and Lajos 2012) We sought to empower knowledge workers by taking a system oriented approach to the development of a personal knowledge organization tool called WikiNizer, (wikinizer.com). WikiNizer is a visual-wiki like, computer enhanced knowledge management environment, built in a new holistic way (Lajos and Benedek, 2013) designed to help us develop and visualize our conceptualizations as we pursue sense making. ...
We illustrate, with use cases supplied by a new personal knowledge organization tool called WikiNizer (wikinizer.com), how visualizing information and its conceptual organization, can help learners and knowledge workers accomplish knowledge organization tasks. The graphic features of WikiNizer, a wiki-like organizer implemented as a graph knowledge base, make visualizations of personal “associative complexes” within shared interests and topics possible, in the form of a Knowledge Graph of ‘Things’. We describe a “Conceptipedia” collaboration concept, applicable not only within the educational field but also in knowledge work in general, which helps us to solve problems visually. Conceptipedia is a collaboration platform which enables WikiNizer users to compare, share, and merge their conceptualization of a domain in the form of meta-knowledge graphs. Conceptipedia helps the user define relations between concepts, and provides interactions which can be coupled with different collaboration techniques. Developing mappings between the meta-structures of the emergent graphs makes conceptualization intellectually manageable, and turns semantic structures into visual Knowledge Architectures that consolidate ontological relations. The collaborative epistemology of Conceptipedia co-evolves commensurate meta-structures to the mutual benefit of its users. Sense-making, by researching, exploring, capturing, articulating, mapping, visualizing and merging conceptual (meta)-structures and relationships can become a social process of consensus building.
Keywords: Intelligence Augmentation, conceptualization, collaborative knowledge management, knowledge architecture, visualization, Wiki, WikiNizer, Conceptipedia, experimental epistemology, personal digital archive, bootstrapping.
... Douglas Engelbart in his "Mother of all Demos" at Stanford University in 1968 described knowledge as a connected graph of concepts which (when it's contents are combined with a personal history of meaning construction) "show rather than tell" 1 what is meaningful to the user. [6] In accordance with Engelbart we adopt a co-evolutionary augmentation research approach [7,8]. We use "co-evolutionary" in the Engelbartian sense of problem solving which goes hand in hand with the development of tools that enhance knowledge work effectiveness in a variety of different contexts. ...
Information technology helps us extend, deepen, and share our knowledge. We claim that visual tools not only enhance our capacity to formulate and share our explicit knowledge, they also help us to activate and transfer our tacit knowledge. Graph based visual structures enable knowledge workers to generate " associate complexes " which can be " bootstrapped " into networked learning environments that document and enhance knowledge building. WikiNizer™Research creates graph based visual structures that articulate the structures and relationships which exist within knowledge domains, and help the emergence of concepts as visual networks trace interpersonal knowledge trails. Although it is only one of the tools in the WikiNizer™ box [wikinizer.com], WikiNizer™Research, by enabling its users to visualise me-ta-structures and conceptual relationships, facilitates interpretations through emerging and co-evolving meta-levels. Because it combines Wiki-like organization with semantic structures, the externalization of our concept structures relates their content to other research, and makes interpretations explicitly comparable at the meta level. It exhibits their semantic patterns and gives us a tool which helps us track meaning construction. In short, WikiNizer™ Research helps us to articulate, organize, and document our ideas, and empower tacit dimensions of our personal knowledge. Outline In this paper we outline our understanding of Personal Knowledge Management, and propose a solution for its augmentation. Focusing on the relationship between personal knowledge and computer conceptualization, we supply a brief description of our product-WikiNizer™Research. Since Cunningham invented the Wiki many Knowledge Management developers have ventured down the Wiki way. In this respect we are no different. We share the belief that Wiki-like organization can enhance conceptualization processes, and after giving an update on our current work, we briefly discuss related work. We conclude by noting that we are heading towards the goal of implementing a collaborative knowledge building model (which is described in earlier papers) called Conceptipedia. [1, 2]
... However, intent and context dependence proved to be the main reasons, in addition to the needs of knowledge discovery and collaborative content creation, why ontologies have to be evolvable and changeable via revision and refactoring. [1,39,43] These requirements imply the integration of KO capabilities not just in "design time" but at run time and, in the collaborative case, "on the fly" throughout the whole 'life cycle' of the ontology. [63] This way, dynamic ontology building and maturing [42] arrived at technologies for permanent refactoring with open ended lifeline including the possibility of bootstrapping the ontology management framework. ...
... For this reason recent efforts in visual KO point to a more flexibleapproach to conceptualization. [1,54,55,56] These works are seeking situated, goal directed, cooperative, approaches to knowledge exploration and a dialogical, interactive emergent semantics that assumes, from the point of view of web based KO, a "self-supporting" [55] bootstrappable ontology authoring environment. [48, 51?] Emergent "bottom up", evolutionary semantics, "refers to a set of principles and techniques analyzing the evolution of decentralized semantic structures in large scale distributed information systems" in which representation of semantics and the discovery of the proper interpretation go hand in hand. ...
... This can be stated as the methodological requirement of the "primacy of bottom up live development": the characteristics of instance descriptions and the relationship with other instances should not be lost as we construct conceptualizations that are applicable to the class of things that are being described. Hence, instead of "conceptual atomism" [2] and correspondences between descriptions and some aspects of reality, KO seeks to establish correspondence between the structure including the relationships between instances and their class models in a more abstract sense of 'images', or using a current term 'visual models of reality', in the spirit of Hertz's Principles of Mechanics 1 . In the process of KO the formation of these 'images' is however, much closer both historically and methodologically, to Whewell's "consilience of inductions" trough the "colligation of facts". ...
Conceptualization and Visual Knowledge Organization are overlapping research areas of Intellect Augmentation with hot topics at their intersection which are enhanced by proliferating issues of ontology integration. Knowledge organization is more closely related to the content of concepts and to the actual knowledge items than taxonomic structures and ‘ontologies’ understood as “explicit specifications of a conceptualization” (Gruber). Yet, the alignment of the structure and relationship of knowledge items of a domain of interest require similar operations. We reconsider ontology-based approaches to collaborative conceptualization from the point of view of user interaction in the context of augmented visual knowledge organization. After considering several formal ontology based approaches, it is argued that co-evolving visualization of concepts are needed both at the object and meta-level to handle the social aspects of learning and knowledge work in the framework of an Exploratory Epistemology. Current systems tend to separate the conceptual level from the content, and the context of logical understanding from the intent and use of concepts. Besides, they usually consider the unification of individual contributions in a ubiquitous global representation. As opposed to this God's eye view we are exploring new alternatives that aim to provide Morphic-like live, tinkerable, in situ approaches to conceptualization and its visualization and to direct manipulation based ontology authoring capabilities. They are uniformly applicable and user-extendable through meta-design both at the content, as well as all emergent conceptual meta-levels, within collaborative frameworks like Conceptipedia. In such a framework negotiation games played at the meta-level of knowledge items can support emergent conceptualization until viable alternative taxonomic structures emerge and workable situated ideas win out. Distributing the workload and responsibility through Crowd Authoring, concept alignment and challenges of social, collaborative concept matching and revision can be addressed in a knowledge management kernel which is also capable to supplement education technology.
Keywords: Conceptualization, Visual Knowledge Organization, Exploratory Epistemology, Ontology Engineering, Ontology Integration, Traversal Frequency, Knowledge Graph, Morphic, Augmentation
... In an earlier paper we spelt out our vision of what a "Next generation concept organization tool" should be. (Benedek and Lajos, 2012) We took a system oriented approach to the development of a personal knowledge management tool, WikiNizer, [wikinizer.com] in order to empower knowledge workers who want to take part in the global knowledge economy. WikiNizer is a visual-wiki like computer enhanced knowledge management environment built in a new holistic way. ...
... In [1] we set out our vision of what is required for building Augmented Knowledge Architectures as Next-Generation Knowledge Management Platforms. At a very high level these requirements can be summarised as follows: ...
In an earlier paper [ICERI2012] we set out our vision of what is required for Next-Generation Concept Organization Platforms. Our requirements build on Engelbart's 1962 Conceptual Framework for Augmenting Human Intellect. They reflect on the technical and conceptual possibilities of updating and realizing Engelbart's 50 year old vision.
We identify End user Development and Meta-design as key conceptual ingredients within a Semantic Wiki like organization of content and meta all levels. Given the current availability of open source enterprise grade web scale tools and technologies for new collaborative ways to develop Internet applications, that can scale to millions of users and creating Semantically rich Giant Global Graph of data. These technologies make it possible to get WikiNizer, our Personal Knowledge Augmentation Engine off the ground and into the Cloud.
In this paper we report on early promising experiences with WikiNizer @ wikinizer.com, the Wiki like organizer of ideas, notes, web research forming Outlines and Structured Documents that incorporate a Semantic Web of non-linear links. The graphic features of WkiNizer make visualizations and collaboration possible on shared interests and topics and developing mappings between personal conceptualizations in the form of consolidated emergent ontologies of relations.
Meta-design empower users to extend existing shared meta-reflective system capabilities with personalized ways of creating new semantic structures, and the means to manage, present, exploit, and share them, creating a foundation on which the next round of development can build. It opens up the possibility of WikiNizer becoming through collaboration and bootstrapping, the Knowledge Augmentation Engine of choice.
keywords: computer supported personal work, augmentation, meta design, end user development, wikinizer, semantic web, knowledge graph, visualization, html 5.
We illustrate, with use cases supplied by a new personal knowledge organization tool called WikiNizer (wikinizer.com), how visualizing information and its conceptual organization, can help learners and knowledge workers accomplish knowledge organization tasks. The graphic features of WikiNizer, a wiki-like organizer implemented as a graph knowledge base, make visualizations of personal "associative complexes" within shared interests and topics possible, in the form of a Knowledge Graph of 'Things'. We describe a "Conceptipedia" collaboration concept, applicable not only within the educational field but also in knowledge work in general, which helps us to solve problems visually. Conceptipedia is a collaboration platform which enables WikiNizer users to compare, share, and merge their conceptualization of a domain in the form of meta-knowledge graphs. Conceptipedia helps the user define relations between concepts, and provides interactions which can be coupled with different collaboration techniques. Developing mappings between the meta-structures of the emergent graphs makes conceptualization intellectually manageable, and turns semantic structures into visual Knowledge Architectures that consolidate ontological relations. The collaborative epistemology of Conceptipedia co-evolves commensurate meta-structures to the mutual benefit of its users. Sense-making, by researching, exploring, capturing, articulating, mapping, visualizing and merging conceptual (meta)-structures and relationships can become a social process of consensus building.
