Contents
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From the ROADMAP FOR ACTION report —
Conduct A Data Inventory
A common-sense response to the increasing volumes of data collected across campuses and the rising deployment of data analytics tools.
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Community Actions
Realign Stakeholder Relationships
These community-based actions portend several possible realignments within the academic community and its stakeholder groups that should also be considered as efforts move forward.
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Community Actions
Leverage Policy to Support Community Control
Another avenue to expand community’s control over data infrastructure is to advocate for favorable federal and state policies.
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Community Actions
Collectively Implement Strategic Practices
Broad adoption of common terms and conditions will have a market effect that favors products and services that are in the best interests of the academic community. This includes advantaging Open Source software over “black-box” algorithms and leveling the playing field for community-owned tools to compete with commercial options whenever available.
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Risk Mitigation
Engage in Open Procurement Practices
An important area when institutions can assert control of data is through purchasing and procurement processes. These processes should be revisited and revised to ensure that they are transparent, competitive, and fully coordinated across the institution.
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Risk Mitigation
Revise Privacy Policies
The development of strong privacy policies is critical, and must extend beyond legal compliance.
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Risk Mitigation
Revise Data Policies
It is critical for data policies to be revised to address the myriad strategic questions raised by the proliferation of data and data analytics.
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Risk Mitigation
Establish Campus Coordination Mechanisms
Coordination mechanisms to adjudicate conflicts among departments and offices will become key as increasing volumes of data are collected across campuses and data analytics tools are deployed.
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Risk Mitigation
Conduct A Data Inventory
A common-sense response to the increasing volumes of data collected across campuses and the rising deployment of data analytics tools.
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What Do We Mean By Data And Data Infrastructure
We talk about two types of data. The first is Research Data, which refers to the data academic institutions generate through their research activities. The second is Grey Data, which refers to the vast amount of data produced by universities outside of core research activities.
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Research Companies
Background
The paradox of the STM publishing industry is that because of multi-year contracts there is very high visibility over its revenues for the next two to three years, but very little beyond this time frame.
