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生物医学数据发现索引DataMed的用户需求分析与可用性评估

User needs analysis and usability assessment of DataMed - a biomedical data discovery index.

作者信息

Dixit Ram, Rogith Deevakar, Narayana Vidya, Salimi Mandana, Gururaj Anupama, Ohno-Machado Lucila, Xu Hua, Johnson Todd R

机构信息

University of Texas Health Science Center at Houston, School of Biomedical Informatics, Houston, TX, USA.

University of California San Diego Health System, Department of Biomedical Informatics, La Jolla, CA, USA.

出版信息

J Am Med Inform Assoc. 2018 Mar 1;25(3):337-344. doi: 10.1093/jamia/ocx134.

Abstract

OBJECTIVE

To present user needs and usability evaluations of DataMed, a Data Discovery Index (DDI) that allows searching for biomedical data from multiple sources.

MATERIALS AND METHODS

We conducted 2 phases of user studies. Phase 1 was a user needs analysis conducted before the development of DataMed, consisting of interviews with researchers. Phase 2 involved iterative usability evaluations of DataMed prototypes. We analyzed data qualitatively to document researchers' information and user interface needs.

RESULTS

Biomedical researchers' information needs in data discovery are complex, multidimensional, and shaped by their context, domain knowledge, and technical experience. User needs analyses validate the need for a DDI, while usability evaluations of DataMed show that even though aggregating metadata into a common search engine and applying traditional information retrieval tools are promising first steps, there remain challenges for DataMed due to incomplete metadata and the complexity of data discovery.

DISCUSSION

Biomedical data poses distinct problems for search when compared to websites or publications. Making data available is not enough to facilitate biomedical data discovery: new retrieval techniques and user interfaces are necessary for dataset exploration. Consistent, complete, and high-quality metadata are vital to enable this process.

CONCLUSION

While available data and researchers' information needs are complex and heterogeneous, a successful DDI must meet those needs and fit into the processes of biomedical researchers. Research directions include formalizing researchers' information needs, standardizing overviews of data to facilitate relevance judgments, implementing user interfaces for concept-based searching, and developing evaluation methods for open-ended discovery systems such as DDIs.

摘要

目的

介绍DataMed(一种数据发现索引(DDI),可用于从多个来源搜索生物医学数据)的用户需求和可用性评估。

材料与方法

我们进行了两个阶段的用户研究。第一阶段是在DataMed开发之前进行的用户需求分析,包括对研究人员的访谈。第二阶段涉及对DataMed原型的迭代可用性评估。我们对数据进行了定性分析,以记录研究人员的信息和用户界面需求。

结果

生物医学研究人员在数据发现方面的信息需求复杂、多维度,且受其背景、领域知识和技术经验的影响。用户需求分析验证了对DDI的需求,而DataMed的可用性评估表明,尽管将元数据聚合到通用搜索引擎并应用传统信息检索工具是很有前景的第一步,但由于元数据不完整和数据发现的复杂性,DataMed仍面临挑战。

讨论

与网站或出版物相比,生物医学数据在搜索方面存在明显问题。提供数据不足以促进生物医学数据发现:数据集探索需要新的检索技术和用户界面。一致、完整和高质量的元数据对于实现这一过程至关重要。

结论

虽然可用数据和研究人员的信息需求复杂且多样,但成功的DDI必须满足这些需求并融入生物医学研究人员的流程。研究方向包括将研究人员的信息需求形式化、标准化数据概述以促进相关性判断、实现基于概念搜索的用户界面,以及开发针对开放式发现系统(如DDI)的评估方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a30d/7378884/5593e2e39d7a/ocx134f1.jpg

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本文引用的文献

2
DATS, the data tag suite to enable discoverability of datasets.
Sci Data. 2017 Jun 6;4:170059. doi: 10.1038/sdata.2017.59.
3
Finding useful data across multiple biomedical data repositories using DataMed.
Nat Genet. 2017 May 26;49(6):816-819. doi: 10.1038/ng.3864.
4
Crafting the third century of the National Library of Medicine.
J Am Med Inform Assoc. 2016 Sep;23(5):858. doi: 10.1093/jamia/ocw122.
5
Big Data Application in Biomedical Research and Health Care: A Literature Review.
Biomed Inform Insights. 2016 Jan 19;8:1-10. doi: 10.4137/BII.S31559. eCollection 2016.
6
Enterprise Data Analysis and Visualization: An Interview Study.
IEEE Trans Vis Comput Graph. 2012 Dec;18(12):2917-26. doi: 10.1109/TVCG.2012.219.
7
The center for expanded data annotation and retrieval.
J Am Med Inform Assoc. 2015 Nov;22(6):1148-52. doi: 10.1093/jamia/ocv048. Epub 2015 Jun 25.
8
The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data.
J Am Med Inform Assoc. 2014 Nov-Dec;21(6):957-8. doi: 10.1136/amiajnl-2014-002974. Epub 2014 Jul 9.
9
Specialized tools are needed when searching the web for rare disease diagnoses.
Rare Dis. 2013 May 16;1:e25001. doi: 10.4161/rdis.25001. eCollection 2013.
10
Characterizing Data Discovery and End-User Computing Needs in Clinical Translational Science.
J Organ End User Comput. 2011;23(4):17-30. doi: 10.4018/joeuc.2011100102.

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