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<sitesearch>title=Search this Project</sitesearch>
This DataONE OpenWetWare site contains informal notes for several research projects funded through DataONE. DataONE is a collaboration among many partner organizations, and is funded by the US National Science Foundation (NSF) under a Cooperative Agreement.
- An investigation of if and how individual articles cite datasets.
- Extraction of data from top tier journals with existing data citation policies or affiliation with existing data depositories.
- This data will be used to examine the influence of author background, discipline, time, open access, journal data sharing policies and other factors on the rate of data reuse/sharing.
- Complete listing of current extracted fields is housed on google docs. These are open to suggestion (which are greatly appreciated!) via comments on this page or the google doc. The extracted data for each article is currently housed on my personal computer and will be posted soon.
- Part of a collaborative project with other DataONE interns, focusing on journal/repository metadata (Nic) and reuse of depository datasets (Valerie)
- See the DataONE group Open Notebook for more details.]
- Full details here
- Download journal articles from concurrent issues of selected journals.
- Journals: American Naturalist, Systematic Biology, Molecular Ecology, Ecology, - still deciding on more....please leave me a note for further suggestions to cover the disciplinary spectrum of biology, specifically environmental and earth related journals. (currently considering: Evolution, Genetics, Paleobiology, something GIS/earth, Nature, Science)
- Time: published in 2010
- Data Extraction
- Read through articles manually, with special attention to the Methods and Acknowledgements sections.
- Record information about author, abstract, discipline, funding source, and most importantly, dataset citation (reuse and sharing).
- Specific fields collected
- Collect Issue metadata: included Supplementary Data, Open Access, Article "type" (differs between journals)
- Data coding
- Most data is collected in full sentence or paragraphs of relevant information. This is then coded or used to calculated a standardize field.
- This will (hopefully) progress to an automated database or coding technique.
- Working on automating/expediting this entire process primarily through an Access database and integration with Zotero citation software. Please leave any suggestions on relevant software (text searching, coding, db) and methods.
I am currently in the process of posting all my research notes here. Also, see Correspondence among the entire DataONE group for additional notes.