Posted by: bluesyemre | September 19, 2016

Recommendations concerning an approach to #OpenScience that will contribute to #OpenInnovation

open-science

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(1) What to do about guidelines for “openness in research data” Here, “openness in research data” does not mean making all data open. Instead, it just means that data required for the purposes of contributing to open innovation be shared to a greater extent than it is now. Guidelines will be necessary to determine what kind of data be made open and what kind of data be kept closed, and these guidelines should include descriptions of the data envisioned as being covered, the establishment of embargos, and so on.

(2) How to ensure that incentives for openness are offered To promote openness, research incentives will be required. In addition to convenience in the preparation of academic papers, essential incentives will include (a) the acceleration of research activities through the reuse of research results, (b) virtual observatory and/or laboratory using databases and analytical tools, (c) acquisition of research resources, (d) interdisciplinary integration, and (e) social implementation. In particular, the basis for incentives will be the provision, through the establishment of databases, of a research data infrastructure that enables the resources from other fields to be utilized.

(3) How to allocate the cost of achieving open science The cost of promoting open science includes data production costs, data distribution costs, standardization-related costs incurred by engineers for distribution, and data storage costs. Therefore, to make openness continuous, a balance must be achieved between these costs and the benefits from utilization of data through openness.

(4) The issues of division of labor in research and the careers of researchers As a result of sophistication of research, the traditional system of research, whereby a single researcher performs all process, i.e. produces, distributes, and utilizes data, has been joined by one in which the data producers who conduct experiments or measurements to produce data, the data distributors (data curators) who organize, standardize, etc. data formats, and the data users who analyze open data each have their own separate roles. However, a problem is that in this system, unlike data users, who can make research achievements in the form of academic papers and patents, data producers and data curators find it difficult to establish iii careers as researchers.

(5) The possibilities of open science The Committee conducted a questionnaire survey of scientific associations relating to each of sections I, II, and III. The majority of the scientific associations that responded have already made academic papers as well as digital data such as data and databases relating to academic papers public. Furthermore, at approximately half of them, the establishment of common measurement criteria for each data item means that there is also data that could become even more valuable.

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