A service-based framework for the OAIS model for earth science data management

Abstract

. OASIS defines the SOA as Ba paradigm for organizing and utilizing distributed capabilities that may be under the control of different ownership domains.^Systems designed around the SOA model benefit from improved scalability, flexibility, and agility. This paper applies the SOA model to the OAIS repository to describe how repositories can be implemented and extended through the use of services that may be internal or external to the host institution, including the consumption of network-or cloud-based services and resources. We use the Service Oriented Architecture (SOA) design paradigm to describe a set of potential extensions to OAIS Reference Model: purpose and justification for each extension, where and how each extension connects to the model, and an example of a specific service that meets the purpose.

Dataset Management as a Special Collection

“…OAIS is a framework initially designed 10 to keep data space and was later used by libraries (Consultative Committee for Space Data Systems 2002). OAIS is probably the most universal model because it can be adapted to be used in different approaches such as archival sounds (Rodríguez 2016) or as a framework for data science management (Flathers, Kenyon, and Gessler 2017). However, the OAIS model is not an application model and questions about it remain unresolved (Cruz and Díez 2016).…”

Research on the Innovation of Science and Technology Management Data Service Mode under Artificial Intelligence Technology

“…Two simulated smart home case studies confirm the effectiveness of the approach through the evaluation of the DDS. Literature [12] designs systems around the SOA model benefiting from improved scalability, flexibility and agility, proposing the application of the SOA model to OAIS repositories, which can be implemented and extended by serving data internally or externally to the host organization. Literature [13] envisioned a customeraware regulatory model to address consumer electricity bill payment and understanding of electricity usage, and in order to make the solution easily accessible, consumer-related electronic data is stored on various servers in different locations of the cloud, with a dedicated administrator who provides management service requests to interface with the method, and through the collation of feedback from surveys, it is argued that the method can provide guaranteed data services.…”

Confronting Climate Change Challenges to Dryland Cereal Production: A Call for Collaborative, Transdisciplinary Research, and Producer Engagement

“…It aimed to improve knowledge of the production systems, identify opportunities to improve their efficiency and sustainability, promote farmer participation, provide decision support tools, educate producers and citizens at all levels. The conceptual framework, outputs and outcomes of the REACCH project can be accessed through its web site: https://www.reacchpna.org, and in publications, including some appearing in this special issue of Frontiers in Ecology and Evolution: (1) Develop a theoretical framework integrating cropping system, economic and climate modeling (Abatzoglou et al, 2014;Antle et al, 2017;Stöckle et al, 2017), (2) Monitor greenhouse gas (GHG) emissions and nitrogen and carbon dynamics in the production systems (Chi et al, , 2017Waldo et al, 2016;Kostyanovsky et al, 2017), (3) Compare current and aspirational production systems for productivity and GHG emission potential under current and projected climate Brown et al, 2017;Maaz T. M. et al, 2017;Stöckle et al, 2017), (4) Address the environmental, social, and economic factors influencing agriculture and technology adoption (Antle et al, 2017;Karimi et al, 2017;Kaur et al, 2017), (5) Anticipate climate change related changes in crop protection requirements (Davis et al, 2015a(Davis et al, ,b, 2017Eigenbrode et al, 2015;Foote et al, 2017), (6) Work closely with producers to develop and guide project activities (Kruger and Yorgey, 2017;Yorgey et al, 2017), (7) Educate students from elementary through graduate levels to prepare coming generations for challenges related to climate change in agriculture (White et al, 2014), (8) Ensure data from the project and related projects are managed to facilitate detecting trends and interdisciplinary collaboration (Flathers et al, 2017), and (9) Coordinate all these activities under an integrated, transdisciplinary framework Morton et al, 2015).…”