The Knowledge Management Methodologies (details below) I enjoy working with are interpreting, explaining, and applying knowledge sharing techniques; and applying narrative, storytelling and interviewing techniques.
Within the foodshed project, I was the information science team member and was able to brief my colleagues on various knowledge sharing, narrative, and interviewing techniques, then recommend and apply the knowledge management strategies to our interviews, narratives, and shared collaborative data. The data we managed included contact information, land size, amounts of food produced, types of food produced, time span in operation, farm name, prices of food, and more. With such a heterogeneous data set, it took care and consideration to manage it accurately, particularly with multiple people working to collect the data.
In the poster Combating Zone Creep with Big Data I worked with knowledge mapping, knowledge sharing, narrative, storytelling, and human-computer interaction options. The poster represents my published effort, which was appropriate at the time; however, since then I have been able to find additional ways to work with the ideas represented in the poster in a more dynamic way through using knowledge management methodologies.
- interpret, explain, and apply knowledge sharing techniques.
- explain and apply knowledge assessment, knowledge assets, and knowledge retention.
- explain and apply KM best practices.
- explain and apply narrative, storytelling, and interviewing techniques.
- explain and apply knowledge (concept) mapping.
- select, interpret, and apply human computer interaction (HCI) techniques.