Making open data work for plant scientists (Record no. 62376)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02305nam a2200217Ia 4500 |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Leonelli Sabina et al. |
| 245 #0 - TITLE STATEMENT | |
| Title | Making open data work for plant scientists |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher | Journal of Experimental Botany |
| Year of publication | 2013 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 4109-4117 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Despite the clear demand for open data sharing, its implementation within plant science is still limited. this is, at least in part, because open data-sharing raises several unanswered questions and challenges to current research practices. In this commentary,some of the challenges encountered by plant researchers at the bench when generating, interpreting, and attempting to disseminate their data have been highlighted. The difficulties involved in sharing sequencing, transcriptomics, proteomics, and metabolomics data are reviewed. The benefits and drawbacks of three data-sharing venues currently available to plant scientists are identified and accessed: (i) journal publication; (ii) university respositories; and (ii) community and project-specific databases. It is concluded that community and project-specific databases are the most useful to researchers interested in effective data sharing, since these databases are explicitly created to meet the researchers needs, support extensive curation, and embody a heightened awareness of what it takes to meet data reusable by others. Such bottom-up and community-driven approaches need to bevalued by the research community, supported by publishers, and provided with long-term sustainable support by funding bodies and government. At the same time, these databases need to be linked to generic databases where possible, in order to be discoverable to the majority of researchers and thus promote effective and efficient data sharing. As we look forward to a future that embraces open access to data and publications, it is essential that data policies, data curation, data integration, data infrastructure, and data funding are linked togrther so as to foster data access and research productivity. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Data sharing |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Databases |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Metabolomics |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Open data |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Proteomics |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Publication |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Repositories |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Transcriptomics |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Journals |
| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Date acquired | Serial Enumeration / chronology | Koha item type |
|---|---|---|---|---|---|---|---|---|
| Journals | RRII Library | RRII Library | 21/03/2014 | Volume 64, Issue 14 | Journals |