harness the collective intelligence of your organization

Jumper 2.0 is a next-generation Knowledge Management tool that allows users to tag any content, media, or data with the relevant knowledge they posses. These tags capture much more than just conventional keywords, knowledge tags are an expanded form of tagging that captures a broad array of knowledge about the information itself. The infomation resource, and the tagged knowledge, is then shared through a collaborative bookmarking engine.

"Knowledge tags are more than traditional non-hierarchical keywords or terms. They are a type of metadata that captures knowledge in the form of descriptions, categorizations, classifications, semantics, comments, notes, annotations, hyperdata, hyperlinks, or references that are collected in tag profiles. These tag profiles reference an information resource that resides in a distributed, and often heterogeneous, storage repository."
The following description is pulled from Wikipedia. You can read more here.

At Jumper, we viewed tags as having much more potential than just a non-hierarchical keyword or term assigned to a piece of information. It could be leveraged to provide a wealth of information about structured and semi-structured content, media or data allowing for it to be more easily discovered and repurposed.

Jumper 2.0 expands on the basic premise of tagging. It takes the concept beyond just web pages to include any information; including relational tables, flat files, images, video, drawings, and documents. Jumper allows end-users to directly tag any information resource stored in any format, on any vendor platform, in any location. User-created tag profiles capture knowledge about the information in remote storage, user contributed information adds real-world knowledge about the resources, and user-created reviews sort out the worthy resources from the inadequate. Tag profiles can grow organically and collect knowledge from many different users. One user might tag the data with keywords only, another user will add a description, a third user could annotate the data, a fourth might add some metadata. It is this ability for the tag profiles to grow overtime that creates a truly collaborative collective intelligence. The tag fields can be customized by customers to meet the unique requirements of the business.

Something Completely New
Jumper knowledge tagging is a new knowledge management discipline that leverages Enterprise 2.0 methodologies. It encourages end users to contribute thier experience, expertise, or insights about an information resource. Jumper 2.0 allows for greater flexibility than more traditional knowledge management classification systems, while still allowing KMers the necessary control to avoid organizational chaos.

Jumper is part of a new wave of business communication tools that allow for more spontaneous, knowledge-based collaboration. Jumper changes the way people discover and share information - it uses a bottom-up community, or social networking approach, rather than the more traditional top-down editorial approach. Community-based tagging increases both the richness and breadth of search. Allows users to determine what is important, and aggregates the knowledge that resides in abundance across your organization.

The power of Jumper resides in direct end-user contributions. It captures the collective knowledge learned about and derived from the data itself. It is this aspect that has the potential to greatly diminish hierarchy, credentialism, and other means by which companies have traditionally been controlled -- in short, the established social order that has traditionally isolated data in silos both technically and procedurally.

Jumper is a more participative and emergent version of knowledge management with its superior ability to capture tacit knowledge, best practices, and relevant experiences from throughout an organization and make them readily available to more users.

the collective power of knowledge

Meaning extraction is an emerging technology that identifies elements of information and concepts contained within documents, images, media, and data, and captures these informative elements and concepts that imply meaning in the context of the business, professional, or technical purpose of the search process. Meaning extraction is more than just full text search. It is applying the tacit, anecdotal, and expectational knowledge of the organization to the search. Beyond keywords and text strings search results must be filtered using more sophisticated knowledge capture techniques. Universal search in Jumper dramatically improves and accelerates a searcher’s ability to gain insight into a topic and answer specific research questions.

Read the Jumper Overview.