Measuring success for a future vision: Defining impact in science gateways/virtual research environments

Prasad Calyam; Nancy Wilkins-Diehr; Mark Miller; Emre H. Brookes; Ritu Arora; Amit Chourasia; Douglas M. Jennewein; Viswanath Nandigam; M. Drew LaMar; Sean B. Cleveland; Greg Newman; Shaowen Wang; Ilya Zaslavsky; Michael A. Cianfrocco; Kevin Ellett; David Tarboton; Keith G. Jeffery; Zhiming Zhao; Juan González-Aranda; Mark J. Perri; Greg Tucker; Leonardo Candela; Tamas Kiss; Sandra Gesing

doi:10.1002/cpe.6099

Measuring success for a future vision: Defining impact in science gateways/virtual research environments

Prasad Calyam
, Nancy Wilkins-Diehr
, Mark Miller
, Emre H. Brookes
, Ritu Arora
, Amit Chourasia
, Douglas M. Jennewein
, Viswanath Nandigam
, M. Drew LaMar
, Sean B. Cleveland
, Greg Newman
, Shaowen Wang
, Ilya Zaslavsky
, Michael A. Cianfrocco
, Kevin Ellett
, David Tarboton
, Keith G. Jeffery
, Zhiming Zhao
, Juan González-Aranda
, Mark J. Perri

Greg Tucker, Leonardo Candela, Tamas Kiss, Sandra Gesing

Chemistry and Biochemistry

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

Abstract

Scholars worldwide leverage science gateways/virtual research environments (VREs) for a wide variety of research and education endeavors spanning diverse scientific fields. Evaluating the value of a given science gateway/VRE to its constituent community is critical in obtaining the financial and human resources necessary to sustain operations and increase adoption in the user community. In this article, we feature a variety of exemplar science gateways/VREs and detail how they define impact in terms of, for example, their purpose, operation principles, and size of user base. Further, the exemplars recognize that their science gateways/VREs will continuously evolve with technological advancements and standards in cloud computing platforms, web service architectures, data management tools and cybersecurity. Correspondingly, we present a number of technology advances that could be incorporated in next-generation science gateways/VREs to enhance their scope and scale of their operations for greater success/impact. The exemplars are selected from owners of science gateways in the Science Gateways Community Institute (SGCI) clientele in the United States, and from the owners of VREs in the International Virtual Research Environment Interest Group (VRE-IG) of the Research Data Alliance. Thus, community-driven best practices and technology advances are compiled from diverse expert groups with an international perspective to envisage futuristic science gateway/VRE innovations.

Original language	English
Article number	e6099
Journal	Concurrency and Computation: Practice and Experience
Volume	33
Issue number	19
DOIs	https://doi.org/10.1002/cpe.6099
State	Published - Oct 10 2021

Funding

The work of Calyam was supported by NSF under Grant/Award OAC‐1730655; the work of Wilkins‐Diehr was supported by NSF under Grant/Award ACI‐1547611; the work of Miller was supported by NSF under Grant/Award ABI‐19054444, NSF under Grant/Award DBI‐1759844, and NIH under Grant/Award R01 GM126463; the work of Brookes was supported by NSF under Grant/Award CHE‐1265817, OAC‐1740097, OAC‐1912444 and NIH GM120600; the work of Arora was supported by NSF under Grant/Award OAC‐1642396; the work of Chourasia was supported by NSF under Grant/Award OAC‐1443083, ACI‐1235505; the work of Jennewein was supported by NSF under Grant/Award MRI‐1626516; the work of Nandigam was supported by NSF under Grant/Award EAR‐1557484, EAR‐1557319, EAR‐1557330; the work of LaMar was supported by NSF under Grant/Award DBI‐1346584, DUE‐1446269, DUE‐1446258, DUE‐1446284; the work of Cleveland was supported by NSF under Grant/Award ACI‐1557349; the work of Newman was supported by NSF under Grant/Award ACI‐1550463, OAC‐1835574; the work of Wang was supported by NSF under Grant/Award ACI‐1047916; the work of Zaslavsky was supported by NSF under Grant/Award ICER‐1639764, ICER‐1639775, ICER‐1639557; the work of Cianfrocco was supported by NSF under Grant/Award ABI‐1759826; the work of Ellett was supported by DOE DE‐PI0000017 via West Virginia University Research Corporation; the work of Tarboton was supported by NSF under Grant/Award ACI 1148453, ACI 1148090, OAC‐1664061, OAC‐1664018, OAC‐1664119; the work of Tucker was supported by NSF under Grant/Award EAR‐1831623, ACI‐1450409; the work of Jeffery was supported by EU H2020 676247; the work of Kiss was supported by EC H2020 826093. information National Science Foundation, OAC-1730655; NSF, ACI-1148090; ACI-1547611; EAR-1831623; EC H2020 826093; OAC-1664119; ABI-1759826; ABI-19054444; ACI-1148453; ACI-1047916; ACI-1235505; ACI-1450409; ACI-1550463; ACI-1557349; CHE-1265817; DBI-1346584; DBI-1759844; DUE-1446258; DUE-1446269; DUE-1446284; EAR-1557319; EAR-1557330; EAR-155748; EU H2020 676247; ICER-1639557; ICER-1639764; ICER-1639775; MRI-1626516; NIH-GM120600; NIH R01 GM126463; OAC-1443083; OAC-1642396; OAC-1664018; OAC-1664061; OAC-1740097; OAC-1835574; OAC-1912444; West Virginia University Research Corporation, DOE DE-PI0000017The work of Calyam was supported by NSF under Grant/Award OAC-1730655; the work of Wilkins-Diehr was supported by NSF under Grant/Award ACI-1547611; the work of Miller was supported by NSF under Grant/Award ABI-19054444, NSF under Grant/Award DBI-1759844, and NIH under Grant/Award R01 GM126463; the work of Brookes was supported by NSF under Grant/Award CHE-1265817, OAC-1740097, OAC-1912444 and NIH GM120600; the work of Arora was supported by NSF under Grant/Award OAC-1642396; the work of Chourasia was supported by NSF under Grant/Award OAC-1443083, ACI-1235505; the work of Jennewein was supported by NSF under Grant/Award MRI-1626516; the work of Nandigam was supported by NSF under Grant/Award EAR-1557484, EAR-1557319, EAR-1557330; the work of LaMar was supported by NSF under Grant/Award DBI-1346584, DUE-1446269, DUE-1446258, DUE-1446284; the work of Cleveland was supported by NSF under Grant/Award ACI-1557349; the work of Newman was supported by NSF under Grant/Award ACI-1550463, OAC-1835574; the work of Wang was supported by NSF under Grant/Award ACI-1047916; the work of Zaslavsky was supported by NSF under Grant/Award ICER-1639764, ICER-1639775, ICER-1639557; the work of Cianfrocco was supported by NSF under Grant/Award ABI-1759826; the work of Ellett was supported by DOE DE-PI0000017 via West Virginia University Research Corporation; the work of Tarboton was supported by NSF under Grant/Award ACI 1148453, ACI 1148090, OAC-1664061, OAC-1664018, OAC-1664119; the work of Tucker was supported by NSF under Grant/Award EAR-1831623, ACI-1450409; the work of Jeffery was supported by EU H2020 676247; the work of Kiss was supported by EC H2020 826093. National Science Foundation, OAC‐1730655; NSF, ACI‐1148090; ACI‐1547611; EAR‐1831623; EC H2020 826093; OAC‐1664119; ABI‐1759826; ABI‐19054444; ACI‐1148453; ACI‐1047916; ACI‐1235505; ACI‐1450409; ACI‐1550463; ACI‐1557349; CHE‐1265817; DBI‐1346584; DBI‐1759844; DUE‐1446258; DUE‐1446269; DUE‐1446284; EAR‐1557319; EAR‐1557330; EAR‐155748; EU H2020 676247; ICER‐1639557; ICER‐1639764; ICER‐1639775; MRI‐1626516; NIH‐GM120600; NIH R01 GM126463; OAC‐1443083; OAC‐1642396; OAC‐1664018; OAC‐1664061; OAC‐1740097; OAC‐1835574; OAC‐1912444; West Virginia University Research Corporation, DOE DE‐PI0000017 Funding information

Funder number
OAC-1664119, ABI‐19054444, ICER-1639557, 1639775, ACI-1550463, CHE-1265817, 1831623, OAC-1443083, MRI‐1626516, DUE-1446269, ACI‐1450409, R01 GM126463, 1948997, ACI-1450409, 1639764, GM120600, ICER‐1639557, EAR-1831623, EAR-1557319, MRI-1626516, DUE‐1446269, OAC-1664061, OAC‐1730655, CHE‐1265817, DUE-1446258, ACI‐1047916, ACI-1148453, EAR-1557484, NIH-GM120600, ACI-1047916, OAC-1740097, OAC-1664018, ICER‐1639764, ACI‐1557349, ICER-1639775, EC H2020 826093, EAR‐1831623, ACI‐1547611, OAC-1642396, 1912444, ACI‐1550463, ACI‐1148090, ACI-1235505, DUE-1446284, EAR‐155748, DBI-1346584, EAR-1557330, ACI-1557349, ABI-1759826, ICER‐1639775, ACI‐1235505, ICER-1639764, OAC-1835574, OAC-1912444, DBI‐1759844
EAR‐1557319, OAC‐1740097, OAC‐1835574, OAC‐1642396, DBI‐1346584, OAC‐1443083, EAR‐1557330, EAR‐1557484, DUE‐1446284, OAC‐1912444, ABI‐1759826
OAC‐1664061, ACI 1148090, DE‐PI0000017, ACI 1148453, OAC‐1664119
676247, 826093

Keywords

futuristic vision
measuring impact
science gateways
success metrics
virtual research environments

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10.1002/cpe.6099

Cite this

Calyam, P., Wilkins-Diehr, N., Miller, M., Brookes, E. H., Arora, R., Chourasia, A., Jennewein, D. M., Nandigam, V., Drew LaMar, M., Cleveland, S. B., Newman, G., Wang, S., Zaslavsky, I., Cianfrocco, M. A., Ellett, K., Tarboton, D., Jeffery, K. G., Zhao, Z., González-Aranda, J., ... Gesing, S. (2021). Measuring success for a future vision: Defining impact in science gateways/virtual research environments. Concurrency and Computation: Practice and Experience, 33(19), Article e6099. https://doi.org/10.1002/cpe.6099

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title = "Measuring success for a future vision: Defining impact in science gateways/virtual research environments",

abstract = "Scholars worldwide leverage science gateways/virtual research environments (VREs) for a wide variety of research and education endeavors spanning diverse scientific fields. Evaluating the value of a given science gateway/VRE to its constituent community is critical in obtaining the financial and human resources necessary to sustain operations and increase adoption in the user community. In this article, we feature a variety of exemplar science gateways/VREs and detail how they define impact in terms of, for example, their purpose, operation principles, and size of user base. Further, the exemplars recognize that their science gateways/VREs will continuously evolve with technological advancements and standards in cloud computing platforms, web service architectures, data management tools and cybersecurity. Correspondingly, we present a number of technology advances that could be incorporated in next-generation science gateways/VREs to enhance their scope and scale of their operations for greater success/impact. The exemplars are selected from owners of science gateways in the Science Gateways Community Institute (SGCI) clientele in the United States, and from the owners of VREs in the International Virtual Research Environment Interest Group (VRE-IG) of the Research Data Alliance. Thus, community-driven best practices and technology advances are compiled from diverse expert groups with an international perspective to envisage futuristic science gateway/VRE innovations.",

keywords = "futuristic vision, measuring impact, science gateways, success metrics, virtual research environments",

author = "Prasad Calyam and Nancy Wilkins-Diehr and Mark Miller and Brookes, \{Emre H.\} and Ritu Arora and Amit Chourasia and Jennewein, \{Douglas M.\} and Viswanath Nandigam and \{Drew LaMar\}, M. and Cleveland, \{Sean B.\} and Greg Newman and Shaowen Wang and Ilya Zaslavsky and Cianfrocco, \{Michael A.\} and Kevin Ellett and David Tarboton and Jeffery, \{Keith G.\} and Zhiming Zhao and Juan Gonz{\'a}lez-Aranda and Perri, \{Mark J.\} and Greg Tucker and Leonardo Candela and Tamas Kiss and Sandra Gesing",

note = "Publisher Copyright: {\textcopyright} 2020 John Wiley \& Sons, Ltd.",

year = "2021",

month = oct,

day = "10",

doi = "10.1002/cpe.6099",

language = "English",

volume = "33",

journal = "Concurrency and Computation: Practice and Experience",

issn = "1532-0626",

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Calyam, P, Wilkins-Diehr, N, Miller, M, Brookes, EH, Arora, R, Chourasia, A, Jennewein, DM, Nandigam, V, Drew LaMar, M, Cleveland, SB, Newman, G, Wang, S, Zaslavsky, I, Cianfrocco, MA, Ellett, K, Tarboton, D, Jeffery, KG, Zhao, Z, González-Aranda, J, Perri, MJ, Tucker, G, Candela, L, Kiss, T & Gesing, S 2021, 'Measuring success for a future vision: Defining impact in science gateways/virtual research environments', Concurrency and Computation: Practice and Experience, vol. 33, no. 19, e6099. https://doi.org/10.1002/cpe.6099

TY - JOUR

T1 - Measuring success for a future vision

T2 - Defining impact in science gateways/virtual research environments

AU - Calyam, Prasad

AU - Wilkins-Diehr, Nancy

AU - Miller, Mark

AU - Brookes, Emre H.

AU - Arora, Ritu

AU - Chourasia, Amit

AU - Jennewein, Douglas M.

AU - Nandigam, Viswanath

AU - Drew LaMar, M.

AU - Cleveland, Sean B.

AU - Newman, Greg

AU - Wang, Shaowen

AU - Zaslavsky, Ilya

AU - Cianfrocco, Michael A.

AU - Ellett, Kevin

AU - Tarboton, David

AU - Jeffery, Keith G.

AU - Zhao, Zhiming

AU - González-Aranda, Juan

AU - Perri, Mark J.

AU - Tucker, Greg

AU - Candela, Leonardo

AU - Kiss, Tamas

AU - Gesing, Sandra

PY - 2021/10/10

Y1 - 2021/10/10

N2 - Scholars worldwide leverage science gateways/virtual research environments (VREs) for a wide variety of research and education endeavors spanning diverse scientific fields. Evaluating the value of a given science gateway/VRE to its constituent community is critical in obtaining the financial and human resources necessary to sustain operations and increase adoption in the user community. In this article, we feature a variety of exemplar science gateways/VREs and detail how they define impact in terms of, for example, their purpose, operation principles, and size of user base. Further, the exemplars recognize that their science gateways/VREs will continuously evolve with technological advancements and standards in cloud computing platforms, web service architectures, data management tools and cybersecurity. Correspondingly, we present a number of technology advances that could be incorporated in next-generation science gateways/VREs to enhance their scope and scale of their operations for greater success/impact. The exemplars are selected from owners of science gateways in the Science Gateways Community Institute (SGCI) clientele in the United States, and from the owners of VREs in the International Virtual Research Environment Interest Group (VRE-IG) of the Research Data Alliance. Thus, community-driven best practices and technology advances are compiled from diverse expert groups with an international perspective to envisage futuristic science gateway/VRE innovations.

AB - Scholars worldwide leverage science gateways/virtual research environments (VREs) for a wide variety of research and education endeavors spanning diverse scientific fields. Evaluating the value of a given science gateway/VRE to its constituent community is critical in obtaining the financial and human resources necessary to sustain operations and increase adoption in the user community. In this article, we feature a variety of exemplar science gateways/VREs and detail how they define impact in terms of, for example, their purpose, operation principles, and size of user base. Further, the exemplars recognize that their science gateways/VREs will continuously evolve with technological advancements and standards in cloud computing platforms, web service architectures, data management tools and cybersecurity. Correspondingly, we present a number of technology advances that could be incorporated in next-generation science gateways/VREs to enhance their scope and scale of their operations for greater success/impact. The exemplars are selected from owners of science gateways in the Science Gateways Community Institute (SGCI) clientele in the United States, and from the owners of VREs in the International Virtual Research Environment Interest Group (VRE-IG) of the Research Data Alliance. Thus, community-driven best practices and technology advances are compiled from diverse expert groups with an international perspective to envisage futuristic science gateway/VRE innovations.

KW - futuristic vision

KW - measuring impact

KW - science gateways

KW - success metrics

KW - virtual research environments

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U2 - 10.1002/cpe.6099

DO - 10.1002/cpe.6099

M3 - Article

AN - SCOPUS:85097076031

SN - 1532-0626

VL - 33

JO - Concurrency and Computation: Practice and Experience

JF - Concurrency and Computation: Practice and Experience

IS - 19

M1 - e6099

ER -

Measuring success for a future vision: Defining impact in science gateways/virtual research environments

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