Streamline News

Integrating Repository Function with Work Practice

Crossovers with the Repository Project and PERSoNA

Posted by Dawn on July 8, 2008

Streamline aims revolve around tools that can be integrated into staff workflows with the minimum of disruption. The tools themselves should, in some way, make a computer based job easier. The first tool we have decided to develop is aimed at reducing the job of thinking and producing metadata for Learning Objects. Having examined previous packing tools such as eCat and the process of uploading to repositories, which often requires metadata entry, we identified three types of metadata:

  • Always entered data – data that has to be entered each time by the user.
  • One shot data – that which the user needs to supply only once if the system is designed to remember it.
  • Automatically generated data – that which the system can generate by making assumptions, examining the learning object and/or supporting documents and hooking into organisational systems.

How the metadata categories fall into these types of data is determined by the type of environment that the system operates in. But providing the system is flexible enough to degrade from one level to the next all environments can be accounted for. Currently it is being designed as a stand alone desktop application, primarily to test extraction process for keyword metadata. The intention is to transfer it into a web service, which should be straight forward as it is written in Java.

So how does this affect the other two projects? Well it is more closely linked at the moment with the Repository project at the moment. It is envision that it will proved users with a much quick means of generating metadata for depositing in the Repository. But the ideas that have been generated during this develop could also be applied to other types of repository deposit, such as research papers, within those metadata fields that are currently manual input. The Repository selected for use at LeedsMet (IntraLibray) already provides some degree of automation, and user profiling, both of which could be extended.

The second tool, search visualisation, aims to create a “bookshelf browsing” experience from search results. By using latent semantic analysis (LSA) to identify the similarities between documents (offline using a thesaurus) the user can select to browse around the area of their search. Again this is closely linked to the Repository project and is intended to be embedded within the repository to provide alternative view for search results. However the idea behind this, LSA, could be used in many other instances, including clustering tag clouds as I previously mentioned here. This idea nicely links Streamline and PERSoNA in a transfer of technology from one to the other.


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