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Find me the data - Discover and explore Springer Nature’s Scientific Data datasets with the ISA-explorer tool

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posted on 2016-04-12, 19:15 authored by Alejandra Gonzalez-BeltranAlejandra Gonzalez-Beltran, Eamonn MaguireEamonn Maguire, Varsha KhodiyarVarsha Khodiyar, Philippe Rocca-SerraPhilippe Rocca-Serra, David Johnson, Massimiliano Izzo, Andrew Hufton, Susanna-Assunta Sansone
Find me the data - Discover and explore Springer Nature’s Scientific Data datasets with the ISA-explorer tool


Scientific Data is a Springer Nature journal focused on data publication. The main article type is a Data Descriptor, which depicts rigorously described, reusable datasets. Each Data Descriptor is accompanied by metadata represented in the ISA-Tab format, which is a tabular format following the Investigation/Study/Assay model. The ISA-explorer tool [1] uses the information in the Scientific Data ISA-Tab metadata files to facilitate dataset discovery. The tool allows users to filter datasets by different criteria: for example, a specific design type or data stored at a particular repository.. The filters can be combined in a boolean search allowing users to easily and quickly discover specific types of data. The ISA-explorer also offers a generic search box, allowing for keyword-based searches of the ISA-Tab metadata files. Additionally, the tool allows browsing of dataset specific information such as related publications and a visualisation of the distribution of the characteristics of the samples involved in the study generating the data. We have some improvements already planned; for example, showing overall statistics, supporting richer query searches considering the semantics of the data (e.g. query expansion based on synonyms) and relying on richer knowledge representations (such as linkedISA [2]). [1] http://blogs.nature.com/scientificdata/2015/12/17/isa-explorer/ [2] Alejandra González-Beltrán, Eamonn Maguire, Susanna-Assunta Sansone and Philippe Rocca-Serra. linkedISA: semantic representation of ISA-Tab experimental metadata. BMC Bioinformatics 2014, 15(Suppl 14):S4. http://dx.doi.org/10.1186/1471-2105-15-S14-S4



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