Extracting the Structure of Design Information From Collaborative Tagging

Author(s):  
Jitesh H. Panchal ◽  
Matthias Messer

Information representation in engineering design is currently dominated by top–down approaches such as taxonomies and ontologies. While top–down approaches provide support for computational reasoning, they are primarily limited due to their static nature, limited scope, and developer-centric focus. Bottom–up approaches, such as folksonomies, are emerging as means to address the limitations of top–down approaches. Folksonomies refer to collaborative classification by users who freely assign tags to design information. They are dynamic in nature, broad in scope, and are user focused. However, they are limited due to the presence of ambiguities and redundancies in the tags used by different people. Considering their complementary nature, the ideal approach is to use both top–down and bottom–up approaches in a synergistic manner. To facilitate this synergy, the goal in this paper is to present techniques for using dynamic folksonomies to extract global characteristics of the structure of design information, and to create hierarchies of tags that can guide the development of structured taxonomies and ontologies. The approach presented in this paper involves using (a) tools such as degree distribution and K-neighborhood connectivity analysis to extract the global characteristics of folksonomies and (b) set-based technique and hierarchical clustering to develop a hierarchy of tags. The approach is illustrated using data from a collective innovation platform that supports collaborative tagging for design information. It is shown that despite the flat nature of the folksonomies insights about the hierarchy in information can be gained. The effects of various parameters on the tag hierarchy are discussed. The approach has potential to be used synergistically with top–down approaches such as ontologies to support the next generation collaborative design platforms.

2012 ◽  
Vol 16 (3) ◽  
Author(s):  
Charles Dziuban ◽  
Patsy Moskal ◽  
Thomas B. Cavanagh ◽  
Andre Watts

The authors describe the University of Central Florida’s top-down / bottom-up action analytics approach to using data to inform decision-making at the University of Central Florida. The top-down approach utilizes information about programs, modalities, and college implementation of Web initiatives. The bottom-up approach continuously monitors outcomes attributable to distributed learning, including student ratings and student success. Combined, this top-down/bottom up approach becomes a powerful means for using large extant university datasets to provide significant insights that can be instrumental in strategic planning.


2013 ◽  
Vol 9 (1) ◽  
pp. 337-355 ◽  
Author(s):  
Audrey André ◽  
Sam Depauw

AbstractElectoral institutions shape the incentive that elected representatives have to cultivate a personal vote, a geographically concentrated personal vote in particular. But are electoral institutions able to make representatives do what they would not do otherwise and to make them not do what they otherwise would have done? Using data from the cross-national partirep MP survey, it is demonstrated that electoral institutions shape elected representatives’ local orientation. That local orientation decreases as district magnitude grows – regardless of what representatives think about political representation. But representatives’ conceptions of representation do shape their uptake in the legislative arena from their contacts with individual constituents. The effect of the electoral incentive grows stronger as elected representatives think of representation as a bottom-up rather than a top-down process.


Author(s):  
Matthias Messer ◽  
Ju¨rgen Grotepaß ◽  
Ulrich K. Frenzel ◽  
Jitesh H. Panchal

In this paper, we present a work-in-progress web-based framework to enable collective innovation via a combination of top-down structural and bottom-up self-organized processes in global enterprises. Problem: In current organizations, expertise is usually locked in discipline-specific project teams or departments based on existing product portfolios which restricts collective innovation through distributed networks of peers translating into increased innovation. Innovation projects are managed in stage gate processes using tools (such as proprietary project workspaces or product data management) that limit access to solutions on various levels of maturity/abstraction throughout the enterprise. Approach: Our approach to facilitate collective innovation in the early stages of product development involves identification and implementation of the following collective innovation mechanisms a) collective concept creation, b) collective concept selection, and c) collective information management. These innovation mechanisms are being instantiated in a web-enabled COllective INnovation (COIN) framework to synthesize collaborative bottom-up and structured top-down approaches fostering innovation. The COIN framework is thus based on self-organized collective innovation as well as function-based systematic conceptual design approaches thereby embodying both collaborative bottom-up and structured top-down structured aspects. From the proposed approach to collective innovation through innovation mechanisms and web enabled tools for implementing collaborative bottom-up and structured top-down structured aspects, global enterprises can benefit from the COIN-framework in fostering synergetic R&D-collaborations, know-how transfer and technology scouting during the early stages of product development. The value to global enterprises can further be significantly increased through application-tailored subspaces consisting of a collection of entities, loosely related by user-defined information links (e.g., tags), as exemplified for a sealing subspace and corkscrew design example in this paper.


Author(s):  
Yu Zhou ◽  
Guangjian Liu ◽  
Xiaoxi Chang ◽  
Ying Hong

Abstract This paper examines the influence of the interaction of three sources of innovation, namely, top-down (bureaucratic structure), bottom-up (high-involvement HRM) and outside-in (outreaching network), on two stages of firm innovation, i.e. invention and commercialization. Using data from 620 large Chinese companies, we found that there was a synergy between the bureaucratic structure and a high-involvement HRM system in influencing firm innovation. Social networks were most effective in promoting firm innovation in the presence of a high-involvement HRM system. The bureaucratic structure inhibited social networks in contributing to firm innovation. Ideas for future research and practical implications are discussed.


2021 ◽  
Vol 20 (1) ◽  
pp. 23-42
Author(s):  
Lars Magnus Hvattum ◽  
Garry A. Gelade

Abstract Correctly assessing the contributions of an individual player in a team sport is challenging. However, an ability to better evaluate each player can translate into improved team performance, through better recruitment or team selection decisions. Two main ideas have emerged for using data to evaluate players: Top-down ratings observe the performance of the team as a whole and then distribute credit for this performance onto the players involved. Bottom-up ratings assign a value to each action performed, and then evaluate a player based on the sum of values for actions performed by that player. This paper compares a variant of plus-minus ratings, which is a top-down rating, and a bottom-up rating based on valuing actions by estimating probabilities. The reliability of ratings is measured by whether similar ratings are produced when using different data sets, while the validity of ratings is evaluated through the quality of match outcome forecasts generated when the ratings are used as predictor variables. The results indicate that the plus-minus ratings perform better than the bottom-up ratings with respect to the reliability and validity measures chosen and that plus-minus ratings have certain advantages that may be difficult to replicate in bottom-up ratings.


PsycCRITIQUES ◽  
2005 ◽  
Vol 50 (19) ◽  
Author(s):  
Michael Cole
Keyword(s):  
Top Down ◽  

Sign in / Sign up

Export Citation Format

Share Document