Abstract

In recent decades, the research community has been dealing with a growing amount and variety of new research data and derived research information. While primary research data, as derived from instruments, are commonly well maintained, derived research data might not always share the same fate. Scientific studies, resulting in further derived data, what we will call here as research data, does not often share the same attention. Fortunately, in the planetary sciences, most primary research data are commonly freely accessible for researchers to use, while research results have commonly not been re-inserted into the research cycle and a discussion about the process has only recently been initiated but there are not concrete methods or efforts to maintain this derived research data. We here discuss the requirements and needs in the planetary sciences to develop and coordinate a platform for research data and develop this idea using planetary cartographic products as an example of a higher-level research product that undergoes various development stages across different organizational levels. We here will visit the current practice and provide a number of scenarios showing how such a research-data life-cycle could look like in the field of planetary research. In order to develop a conceptual framework, experience from established terrestrial research-data frameworks and spatial data infrastructures are integrated into the discussion.

Highlights

  • In today's research landscape, data obtained and derived through a controlled process are playing a key role for advancing knowledge and for building foundations for future research

  • In order to facilitate our discussion, we need to establish the relationship between research data in general and the concepts of planetary mapping and planetary maps, in particular as the latter are the focus in this investigation

  • The planetary research data development process can be well represented through the concept of the Data-Information-Knowledge-Pyramid (DIK) on one hand, and the concept of the Visualization Pipeline on the other (e.g., Haber and McNabb, 1990; dos Santos and Brodlie, 2004)

Read more

Summary

Introduction

In today's research landscape, data obtained and derived through a controlled process are playing a key role for advancing knowledge and for building foundations for future research. The amount and variety of row data and research data that the research community is dealing with on an everyday basis have been increasing exponentially over the last decades, with unstructured data growing at up to ten times faster rates than structured data (e.g., Zikopoulos et al, 2012; Kitchin, 2014) This development applies to the majority of professional fields targeted at the processing of low-level data to derive meaningful information products for analysis and research. In order to provide platforms to facilitate use and reuse of RD in a transparent and sustainable way, research initiatives such as the Research Data Alliance (RDA) (www.rda-alliance.org), GoFAIR (www.go-fair.org), or CODATA (www.codata.org) have been established, who have been contributing with recommendation and guidelines Some of these initiatives’ higher-level aims are targeted at responding to requirements related to public research funding as communicated by, e.g., OECD (2007). Map compilation refers to a higher-level derivative process that builds upon distillation of original map data, and both need to be carefully distinguished

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call