Loading [a11y]/accessibility-menu.js
Building a Data Ecosystem: A New Data Stewardship Paradigm for the Multi-Mission Algorithm and Analysis Platform (MAAP) | IEEE Conference Publication | IEEE Xplore

Building a Data Ecosystem: A New Data Stewardship Paradigm for the Multi-Mission Algorithm and Analysis Platform (MAAP)


Abstract:

New adaptive approaches to Earth observation data stewardship need to be adopted in order to allow for higher data volumes, heterogeneous data and constantly evolving tec...Show More

Abstract:

New adaptive approaches to Earth observation data stewardship need to be adopted in order to allow for higher data volumes, heterogeneous data and constantly evolving technologies. The data ecosystem approach to stewardship offers a viable solution to this need by placing an emphasis on the relationships between data, technologies and people. In this paper, we present the Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform's (MAAP) creation of a data ecosystem to support global aboveground terrestrial carbon dynamics research. We present the components needed to support the MAAP data ecosystem along with two data stewardship workflows used in the MAAP and the development of extended metadata for MAAP.
Date of Conference: 28 July 2019 - 02 August 2019
Date Added to IEEE Xplore: 14 November 2019
ISBN Information:

ISSN Information:

Conference Location: Yokohama, Japan
References is not available for this document.

1. INTRODUCTION

Earth observation data volumes have grown exponentially as new platforms with more accurate sensors are launched each year [1]. Upcoming space borne missions, including ESA’s BIOMASS mission and NASA/ISRO’s NISAR mission, will offer unprecedented data about Earth but will also feature exponentially higher data volumes than any currently operating Earth observation mission. In addition, the heterogeneous nature of Earth observation data, which are collected from satellites, aircraft and ground stations at various resolutions, coverages and processing levels, makes analyzing these data a challenge for scientists.

Select All
1.
S. Nativi, P. Mazzetti, M. Santoro, F. Papeschi, M. Craglia and O. Ochiai, "Big Data challenges in building the Global Earth Observation System of Systems", Environmental Modelling & Software, vol. 68, pp. 1-26, Jun. 2015.
2.
M. Parsons and P. Fox, "Is Data Publication the Right Metaphor?", Data Science Journal, vol. 12, pp. 32-46, Feb. 2013.
3.
M. Parsons, Ø Godoy, E. LeDrew, T. de Bruin, B. Danis, S. Tomlinson, et al., "A conceptual framework for managing very diverse data for complex interdisciplinary science", Journal of Information Science, vol. 37, no. 6, pp. 555-569, Oct. 2011.
4.
Y. Gil, C. David, I. Demir, B. Essawy, R. Fulweiler, J. Goodall, et al., "Towards the Geoscience Paper of the Future: Best Practices for documenting and sharing research from data to software to provenance", Earth and Space Science, vol. 3, no. 10, pp. 388-415, Oct. 2016.
5.
L. Fatoyinbo, N. Pinto, M. Hofton, M. Simard, B. Blair, S. Saatchi, et al., "The 2016 NASA AfriSAR campaign: Airborne SAR and Lidar measurements of tropical forest structure and biomass in support of future satellite missions", Proc. International Geoscience and Remote Sensing Symposium (IGARSS), 2017.
Contact IEEE to Subscribe

References

References is not available for this document.