{"paper":{"title":"Introducing Data Primitives: Data Formats for the SKED Framework","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.QM","authors_text":"Elizabeth D. Trippe, Jacob B. Aguilar, Jessica A. Brady, Juan B. Gutierrez, Mustafa V. Nural, Yi H. Yan","submitted_at":"2017-06-25T15:54:30Z","abstract_excerpt":"Background: The past few years have seen a tremendous increase in the size and complexity of datasets. Scientific and clinical studies must to incorporate datasets that cross multiple spatial and temporal scales to describe a particular phenomenon. The storage and accessibility of these heterogeneous datasets in a way that is useful to researchers and yet extensible to new data types is a major challenge.\n  Methods: In order to overcome these obstacles, we propose the use of data primitives as a common currency between analytical methods. The four data primitives we have identified are time se"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.08131","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}