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Topics related to distance eLearning in academia and other organizations
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Intro to Nemetics - The Infintely Dynamic Play

"The purpose of using Nemes and Nemetics is coming to grips with ‘emergences’, which I believe is well within the reach of almost everyone on the earth. It helps us better understand events in our lives to take actions that change our future to a more ‘desirable’ one.

 

Let us start by understanding NEME. It is an acronym that stands for:

>> N = Notice

>> E = Engage

>> M = Mull

>> E = Exchange"

 

from source: - http://rmcpl.wordpress.com/

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ghbrett's curator insight, July 8, 2013 8:14 AM

The author goes on to describe the processes and provides some examples as well as a SWF video. It is a long post, but take the time to read it all.

 

As I interpret the notion of #NEMETICS I see it related to a couple things as identifying processes for activities listed near the end of the article. Also, there are mentions of iteration and growth. I reminds me of Jeff Conklin's work ( http://www.cognexus.org/cognexus_institute.htm ) on Dialog Mapping using Compendium ( http://projects.kmi.open.ac.uk/compendium/ ) based on Issue Based Information Systems ( http://en.wikipedia.org/wiki/Issue-Based_Information_System ).

 

My visual would be a 2x2 matrix with N, E, M, E in each of the four squares. There would be a spiral that begins in the lower left of N and then move through the other three squares. Instead of just continuing as one line, there could be multiple branches that continue (iterate) or due to the Exchange would point to other 2x2 matrices of a similar nature.

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NOT-HG-13-003: Request for Information (RFI): Training Needs in Response to Big Data to Knowledge (BD2K) Initiative

"The National Institutes of Health is launching Big Data to Knowledge (BD2K), an initiative to address how best to manage and utilize the large amounts of biomedical data that new technologies can generate (http://www.nih.gov/news/health/dec2012/od-07.htm).

 

... The era of ‘Big Data’ has arrived for biomedical research, bringing with it immense challenges as well as spectacular opportunities. In this context, ‘Big Data’ is meant to reflect the challenges facing biomedical researchers of all stripes in accessing, organizing, analyzing, and integrating datasets that are increasingly larger, more complex, and more numerous. These data are also of diverse types that must be integrated, including imaging, phenotypic, molecular, exposure, health, and many other types of biomedical, behavioral and clinical data. While used here for convenience, the phrase ‘Big Data’ is intended to be shorthand for the reality that biomedical research has become a data-intensive enterprise.

 

Advances in biomedical sciences using Big Data will require more scientists with appropriate expertise and skills, some of whom will be critical members of interdisciplinary teams. NIH is interested in increasing funding for long- and short-term training at all professional levels, in areas essential for accessing, organizing, analyzing, and integrating biomedical Big Data (e.g., computational biology, biostatistics, bioinformatics, the quantitative sciences, and related areas)." - from source: http://grants.nih.gov

ghbrett's insight:

Big Data, data mining, and the aggregation of data from varied resources are becoming more important to the research community. This initiative of NIH should provide findings and information that can transfer and be applied to other communities and agencies.

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GI2MO: Semantically Empowered Idea Management

GI2MO: Semantically Empowered Idea Management | Distance Ed Archive | Scoop.it

"GI2MO aims to improve current Idea Management Systems by providing reboost data integration capabilities and additional data analysis tools though rich metadata descriptions. Both of those features are derived from the use of Semantic Web technologies to interconnect data inside the Idea Management Systems with assets published by other systems and accross the World Wide Web. For details on how it is possible to exploit the benefits of Semantic Web in Idea Management see use cases." from source: http://www.gi2mo.org/

ghbrett's insight:

This is an intersting site and project from the Universidad Politecnica de Madrid (UPM). The site is worth exploring for both the content about ontologies and taxonomy, but the visualizations for models and use cases. Also, they have information about embedding their tool into CMS's and other social media systems to improve analytics and metadata that can help move to next generation Semantic Web prepared applicatioins.

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