Data discovery with DATS: exemplar adoptions and lessons learned.
Data discovery with DATS: exemplar adoptions and lessons learned.
复制标题
数据发现数据：示例采用和经验教训。
DOI：
10.1093/jamia/ocx119
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发表时间：
2018-01-01
期刊：
影响因子：
--
通讯作者：
Rocca-Serra P
中科院分区：
文献类型：
--
作者：
Gonzalez-Beltran AN;Campbell J;Dunn P;Guijarro D;Ionescu S;Kim H;Lyle J;Wiser J;Sansone SA;Rocca-Serra P
数据标签套件(DATS)是一个支持数据集描述、索引和发现的模型。它以带注释的序列化的形式提供，使用的是主要搜索引擎使用的一个词汇表schema.org，因此可以在Web上发现这些数据集。DATS是美国国立卫生研究院大数据到知识数据发现索引原型DataMed的基础，旨在提供一个“数据集的PubMed”。在DataMed中索引各种 >；60存储库时获得的经验有助于评估DATS的实体、属性和范围。在这项工作中，另外3个示范性和多样化的数据源被他们的代表或专家映射到DATS，提供了针对一组新的现有数据的DATS适合度的深入扫描。这一程序，包括用户和实施者的反馈，产生了数据挖掘系统的实施指南和最佳做法，并确定了一条发展和优化该模式的途径。最后，这项工作暴露了在定义用于索引的数据集时的额外需求，特别是在临床和观察性信息的背景下。
The DAta Tag Suite (DATS) is a model supporting dataset description, indexing, and discovery. It is available as an annotated serialization with schema.org, a vocabulary used by major search engines, thus making the datasets discoverable on the web. DATS underlies DataMed, the National Institutes of Health Big Data to Knowledge Data Discovery Index prototype, which aims to provide a “PubMed for datasets.” The experience gained while indexing a heterogeneous range of >60 repositories in DataMed helped in evaluating DATS’s entities, attributes, and scope. In this work, 3 additional exemplary and diverse data sources were mapped to DATS by their representatives or experts, offering a deep scan of DATS fitness against a new set of existing data. The procedure, including feedback from users and implementers, resulted in DATS implementation guidelines and best practices, and identification of a path for evolving and optimizing the model. Finally, the work exposed additional needs when defining datasets for indexing, especially in the context of clinical and observational information.
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影响因子：
9.8
作者：
Johnson AE;Pollard TJ;Shen L;Lehman LW;Feng M;Ghassemi M;Moody B;Szolovits P;Celi LA;Mark RG
通讯作者：
Mark RG
影响因子：
30.8
作者：
Sansone, Susanna-Assunta;Rocca-Serra, Philippe;Field, Dawn;Maguire, Eamonn;Taylor, Chris;Hofmann, Oliver;Fang, Hong;Neumann, Steffen;Tong, Weida;Amaral-Zettler, Linda;Begley, Kimberly;Booth, Tim;Bougueleret, Lydie;Burns, Gully;Chapman, Brad;Clark, Tim;Coleman, Lee-Ann;Copeland, Jay;Das, Sudeshna;de Daruvar, Antoine;de Matos, Paula;Dix, Ian;Edmunds, Scott;Evelo, Chris T.;Forster, Mark J.;Gaudet, Pascale;Gilbert, Jack;Goble, Carole;Griffin, Julian L.;Jacob, Daniel;Kleinjans, Jos;Harland, Lee;Haug, Kenneth;Hermjakob, Henning;Sui, Shannan J. Ho;Laederach, Alain;Liang, Shaoguang;Marshall, Stephen;McGrath, Annette;Merrill, Emily;Reilly, Dorothy;Roux, Magali;Shamu, Caroline E.;Shang, Catherine A.;Steinbeck, Christoph;Trefethen, Anne;Williams-Jones, Bryn;Wolstencroft, Katherine;Xenarios, Ioannis;Hide, Winston
通讯作者：
Hide, Winston
影响因子：
9.8
作者：
Sansone SA;Gonzalez-Beltran A;Rocca-Serra P;Alter G;Grethe JS;Xu H;Fore IM;Lyle J;Gururaj AE;Chen X;Kim HE;Zong N;Li Y;Liu R;Ozyurt IB;Ohno-Machado L
通讯作者：
Ohno-Machado L
影响因子：
9.8
作者：
Wilkinson MD;Dumontier M;Aalbersberg IJ;Appleton G;Axton M;Baak A;Blomberg N;Boiten JW;da Silva Santos LB;Bourne PE;Bouwman J;Brookes AJ;Clark T;Crosas M;Dillo I;Dumon O;Edmunds S;Evelo CT;Finkers R;Gonzalez-Beltran A;Gray AJ;Groth P;Goble C;Grethe JS;Heringa J;'t Hoen PA;Hooft R;Kuhn T;Kok R;Kok J;Lusher SJ;Martone ME;Mons A;Packer AL;Persson B;Rocca-Serra P;Roos M;van Schaik R;Sansone SA;Schultes E;Sengstag T;Slater T;Strawn G;Swertz MA;Thompson M;van der Lei J;van Mulligen E;Velterop J;Waagmeester A;Wittenburg P;Wolstencroft K;Zhao J;Mons B
通讯作者：
Mons B
影响因子：
3.7
作者：
Bandrowski A;Brinkman R;Brochhausen M;Brush MH;Bug B;Chibucos MC;Clancy K;Courtot M;Derom D;Dumontier M;Fan L;Fostel J;Fragoso G;Gibson F;Gonzalez-Beltran A;Haendel MA;He Y;Heiskanen M;Hernandez-Boussard T;Jensen M;Lin Y;Lister AL;Lord P;Malone J;Manduchi E;McGee M;Morrison N;Overton JA;Parkinson H;Peters B;Rocca-Serra P;Ruttenberg A;Sansone SA;Scheuermann RH;Schober D;Smith B;Soldatova LN;Stoeckert CJ Jr;Taylor CF;Torniai C;Turner JA;Vita R;Whetzel PL;Zheng J
通讯作者：
Zheng J