Search and Discovery : OER's Open Loop

Open educational resources (OER) promise increased access, participation, quality, and relevance, in addition to cost reduction. These seemingly fantastic promises are based on the supposition that educators and learners will discover existing resources, improve them, and share the results, resulting in a virtuous cycle of improvement and re-use. By anecdotal metrics, existing web scale search is not working for OER. This situation impairs the cycle underlying the promise of OER, endangering long term growth and sustainability. While the scope of the problem is vast, targeted improvements in areas of curation, indexing, and data exchange can improve the situation, and create opportunities for further scale. I explore the way the system is currently inadequate, discuss areas for targeted improvement, and describe a prototype system built to test these ideas. I conclude with suggestions for further exploration and development.

RDA and Linked Data

Gordon Dunshiren esitys Kuvailupäivillä 25.3.2014 Helsingissä.

An Open Source, DDI-based Curation System for Social Science Data

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Open research data policies, what makes the difference?

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Open Access Research Data Repository for Corpus Linguistic Data – A Modular Approach

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Leveraging open access for integrating repository data at Indiana University Libraries

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Dynamic graphics of parametrically linked multivariate methods used in compositional data analysis

Many multivariate methods that are apparently distinct can be linked by introducing one or more parameters in their definition. Methods that can be linked in this way are correspondence analysis, unweighted or weighted logratio analysis (the latter also known as "spectral mapping"), nonsymmetric correspondence analysis, principal component analysis (with and without logarithmic transformation of the data) and multidimensional scaling. In this presentation I will show how several of these methods, which are frequently used in compositional data analysis, may be linked through parametrizations such as power transformations, linear transformations and convex linear combinations. Since the methods of interest here all lead to visual maps of data, a "movie" can be made where where the linking parameter is allowed to vary in small steps: the results are recalculated "frame by frame" and one can see the smooth change from one method to another. Several of these "movies" will be shown, giving a deeper insight into the similarities and differences between these methods

Introduction to the Semantic Web and the Web of Linked Data

Presentation given as part of the EPrints/dotAC training event on 26 Mar 2010.

Linked Data Infrastructures and HE Challenges

ECSS Talk

Open Equipment data flow

Short set of slides explaining the workflow from a university website to equipment.data.ac.uk

Stream Reasoning with Linked Data

Slides describing streaming data, data stream processing systems and stream reasoning Also we have some description of CSPARQL