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SEAD: White Papers

About this Collection
Edited by Morgan Fritz · 56 resources · Last updated about 10 years ago

The SEAD network is a community of advocates for the importance and value of research and creative work across the arts and sciences. There are two groups funded by NSF EAGER grants: NSEAD and XSEAD. SEAD was adopted to acknowledge that the two groups have linkages. The White Papers project was proposed early on within the NSEAD group as a way to build community around perceived challenges and opportunities relative to engagaing art/design with engineering/science disciplines. The White Papers Working Group is conducting this research for the network going forward, to structure actions and make them relevant to stakeholders. The papers posted here are the response to this open call from our global network. They represent a spectrum of interests in advocating for trans-disciplinarity between arts, sciences, and technologies. The call asked for authors to submit a plan of action and identify stakeholders who might be instrumental in carrying out such plans. The individual efforts do not represent a collective aim towards any explicit initiative. Rather, they offer a broad array of views on barriers faced and prospective solutions. The SEAD White Papers project is not intended to offer direct proposals for funding, though some individual papers may do so. The SEAD network acknowledges that network funding should best be distributed across a range of stakeholders. The White Papers project is not an effort to claim that art advances science or vice versa. Though individual authors may do so, the network is giving voice to opinions individually and collectively. SEAD network, the White Papers Working Group, and the conversations enabled here should be acknowledged as different entities, and the objectives of SEAD not necessarily the same as that of individual suggested actions. For more background on the organization of SEAD please see: http://sead.viz.tamu.edu/pdf/SEAD_Annual_Report_Summary_5_2012.pdf This material is based upon work supported by the National Science Foundation under Grant No.1142510, Collaborative Research: EAGER: Network for Science, Engineering, Arts and Design (NSEAD) IIS, Human Centered Computing. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.