If you build it, promote it, and they trust you, then they will come: Diffusion strategies for science gateways and cyberinfrastructure adoption to harness big data in the science, technology, engineering, and mathematics (STEM) community
If you build it, promote it, and they trust you, then they will come: Diffusion strategies for science gateways and cyberinfrastructure adoption to harness big data in the science, technology, engineering, and mathematics (STEM) community
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如果你构建它、推广它,并且他们信任你,那么他们就会来:科学网关和网络基础设施采用的扩散策略,以利用科学、技术、工程和数学 (STEM) 社区中的大数据
DOI:
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发表时间:
2021
期刊:
影响因子:
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通讯作者:
Kulsawasd Jitkajornwanich
中科院分区:
文献类型:
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作者:
Kerk F. Kee;Bethanie Le;Kulsawasd Jitkajornwanich
In the big data era, for science gateways (SG) and cyberinfrastructure (CI) projects to have the greatest impacts, they need to be widely adopted in the scientific community. However, diffusion activities, or activities aimed to spread SG/CI in the science, technology, engineering, and mathematics community, are often an afterthought in projects. We warn against the fallacy of “If You Build It, They Will Come.” Projects could be intentional in promoting tool adoption. Based on an analysis of 83 interviews with 66 administrators, developers, scientists/users, and outreach educators of SG/CI, we identified seven external communication practices—raising awareness, personalizing demonstrations, providing online and offline training, networking with the community, building relationships with trust, stimulating word‐of‐mouth persuasion, and keeping reliable documentation. With these strategies, we revised the pop culture line to “If You Build It, Promote It, and They Trust You, Then They Will Come.” We also observed the beliefs that external communication is mainly necessary when seeking continuous funding, and it belongs to the skillset of nontechnical staff. These two beliefs may explain why external communication is underemphasized in many SG/CI projects. The article serves as evidence to justify a bigger budget in funding proposals for diffusion strategies to increase adoption and broader impacts.
DOI:
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发表时间:
2018
期刊:
in conjunction with IEEE Big Data
影响因子:
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作者:
Chandrashekara, A.;Talluri, R.;Sivarathri, S.;Mitra, R.;Calyam, P.;Kee, K.;Nair, S.S.
通讯作者:
Nair, S.S.