Amy Nurnberger – InfoDoc MicroVeille

Authors : Philip Espinola Coombs, Christine Malinowski, Amy Nurnberger

Objective

To evaluate library workshops on their coverage of data management topics.

Methods

We used a modified version of Sapp Nelson’s Competency Matrix for Data Management Skills, a matrix of learning goals organized by data management competency and complexity level, against which we compared our educational materials: slide decks and worksheets.

We examined each of the educational materials against the 333 learning objectives in our modified version of the Matrix to determine which of the learning objectives applied.

Conclusions

We found it necessary to change certain elements of the Matrix’s structure to increase its clarity and functionality: reinterpreting the “behaviors,” shifting the organization from the three domains of Bloom’s taxonomy to increasing complexity solely within the cognitive domain, as well as creating a comprehensive identifier schema.

We appreciated the Matrix for its specificity of learning objectives, its organizational structure, the comprehensive range of competencies included, and its ease of use. On the whole, the Matrix is a useful instrument for the assessment of data management programming.

URL : Skills, Standards, and Sapp Nelson’s Matrix: Evaluating Research Data Management Workshop Offerings

Alternative location : https://escholarship.umassmed.edu/jeslib/vol8/iss1/6/

Authors : Sünje Dallmeier-Tiessen, Varsha Khodiyar, Fiona Murphy, Amy Nurnberger, Lisa Raymond, Angus Whyte

The data curation community has long encouraged researchers to document collected research data during active stages of the research workflow, to provide robust metadata earlier, and support research data publication and preservation.

Data documentation with robust metadata is one of a number of steps in effective data publication. Data publication is the process of making digital research objects ‘FAIR’, i.e. findable, accessible, interoperable, and reusable; attributes increasingly expected by research communities, funders and society.

Research data publishing workflows are the means to that end. Currently, however, much published research data remains inconsistently and inadequately documented by researchers.

Documentation of data closer in time to data collection would help mitigate the high cost that repositories associate with the ingest process. More effective data publication and sharing should in principle result from early interactions between researchers and their selected data repository.

This paper describes a short study undertaken by members of the Research Data Alliance (RDA) and World Data System (WDS) working group on Publishing Data Workflows. We present a collection of recent examples of data publication workflows that connect data repositories and publishing platforms with research activity ‘upstream’ of the ingest process.

We re-articulate previous recommendations of the working group, to account for the varied upstream service components and platforms that support the flow of contextual and provenance information downstream.

These workflows should be open and loosely coupled to support interoperability, including with preservation and publication environments. Our recommendations aim to stimulate further work on researchers’ views of data publishing and the extent to which available services and infrastructure facilitate the publication of FAIR data.

We also aim to stimulate further dialogue about, and definition of, the roles and responsibilities of research data services and platform providers for the ‘FAIRness’ of research data publication workflows themselves.

URL : Connecting Data Publication to the Research Workflow: A Preliminary Analysis

DOI : https://doi.org/10.2218/ijdc.v12i1.533