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Illuminating Scholarly Dark Matter

September 14, 2013 Leave a comment

Much of what we know about scholarly communication and the “science of science” relies on  the scholarly record”of journal publications, monographs, and books;  and  upon the patterns of findings, evidence, and collaborations that analysis of this record reveals. In contrast, research data, in its current state, represents a type of  ‘scholarly dark matter’ that underlies the current visible evidentiary relationships among publications. Improved data citation practices have the potential to make this dark matter visible.

Yesterday the Data Science Journal  published a special issue devoted to data citations: Out of Cite, Out of Mind: The Current State of Practice, Policy, and Technology for the Citation of Data. This  is a comprehensive review of data citations principles, practices, infrastructure, policy and research. And I’m very pleased to have contributed to writing and researching  this document  as part of the  CODATA-ICSTI Task Group on Data Citation Standards and Practices. 

This is a rapidly evolving area, and representatives from the CODATA-ICSTI task group,  Force 11, the Research Data Alliance and a number of other groups, have formed a  synthesis group  which is developing an integrated statement of principles  to promote broad adoption of a consistent policy for data citation across disciplines and venues.

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Some Lessons from Crowd-sourced Mapping for Open Government

September 5, 2013 1 comment

My collaborator Michael McDonald  and I have been analyzing the data that resulted from the crowd-sourcing participative electoral mapping projects we were involved in and other public redistricting efforts, and this blog includes two earlier articles from this line of research. In this research article, to appear in the Proceedings of the 47th Annual Hawaii International Conference on System Sciences (IEEE/Computer Society Press) we reflect on initial lessons learned about public participation and technology from the last round of U.S. electoral mapping.

Three major factors influenced the effectiveness of efforts to increase public input into the political process through crowdsourcing. First, open electoral mapping tools were a practical necessity to enable substantially greater levels increase public participation.  Second, the interest and capacity of local grassroots organizations was critical to catalyzing the public to engage using these tools.  Finally, the permeability of government authorities to public input was needed for such participation to have a significant effect.

The impermeability of government to public input in a democratic state can take a number of more-or-less subtle forms, each of which was demonstrated in the last round of electoral mapping: Authorities blatantly resist public input by providing no recognized channel for it; or by creating a nominal channel, but leaving it devoid of funding or process; or procedurally accepting input, but substantively ignoring it

Authorities can also resist public participation and transparency indirectly through the way they make essential information available to the public. For example, mapping authorities that do not wish to have potential political consequences of their plans easily evaluated publicly will not provide election results merged with census geography — although they assuredly use such merged information for internal evaluation of their plans.  Redistricting authorities may purposefully restrict the scope of the information they make available. For example, a number of states chose to make available boundaries and information related to the approved plan only. Another subtle way by which authorities can hinder transparency is by releasing information plans in a non-machine readable format. An even more subtle, but substantial barrier is the interface through which representations of plans are made available.

This resistance appears to have been in large part, effective. Public participation increased by an order of magnitude in the last round of redistricting. However, except in a few exemplary cases, visible direct effects on policy outcomes appears modest. You can find more details, in the article.

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