Resources available for autism research in the big data era: a systematic review

PeerJ

article

Reem Al-jawahiri¹  Elizabeth Milne¹ 

[1] Department of Psychology, University of Sheffield

关键词: Autism spectrum disorder;    ASD;    Data sharing;    Open science;    Subtyping;    Heterogeneous disorders;    Databases;    Neuroimaging data;    Phenotypic data;    Biobanks;   

DOI  :  10.7717/peerj.2880

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Recently, there has been a move encouraged by many stakeholders towards generating big, open data in many areas of research. One area where big, open data is particularly valuable is in research relating to complex heterogeneous disorders such as Autism Spectrum Disorder (ASD). The inconsistencies of findings and the great heterogeneity of ASD necessitate the use of big and open data to tackle important challenges such as understanding and defining the heterogeneity and potential subtypes of ASD. To this end, a number of initiatives have been established that aim to develop big and/or open data resources for autism research. In order to provide a useful data reference for autism researchers, a systematic search for ASD data resources was conducted using the Scopus database, the Google search engine, and the pages on ‘recommended repositories’ by key journals, and the findings were translated into a comprehensive list focused on ASD data. The aim of this review is to systematically search for all available ASD data resources providing the following data types: phenotypic, neuroimaging, human brain connectivity matrices, human brain statistical maps, biospecimens, and ASD participant recruitment. A total of 33 resources were found containing different types of data from varying numbers of participants. Description of the data available from each data resource, and links to each resource is provided. Moreover, key implications are addressed and underrepresented areas of data are identified.

【 授权许可】

CC BY