アカデミックなデータ。データ分析フリーランスの専門家が対応する必要があるのか?

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Research in universities often benefits from the structured environment of academia. Unlike in small business or industry settings, intra-mural (within university) collaborations allow various experts to contribute to the research. Generally, academia does not suffer from a shortage of expertise due to collaborative efforts.

However, not all collaborations succeed and mistakes happen. David Broockmann, a political science expert who was back then a graduate student of UC Berkeley, pointed out irregularities from another political science paper. Such incidences cause embarrassment and hurt the hard earned credibility in academia. Could these incidences be avoided?

データ分析フリーランサー

Several solutions can be proposed to ensure quality data. Hiring a freelance expert to provide データサイエンス related consultations can be one of the solutions. Here we discuss top three reasons for hiring a freelance Ph.D. or post-doc for data science related projects:

  1. a) 柔軟性。 A フリーランスのデータエキスパート can be hired as and when need; further, the tasks that require input from an external freelance expert may vary a lot. For instance, a research group may need an expert to cross check their findings from データ分析; whereas others may need a data scientist to run a part of project. A principal investigator (PI) with a limited budget can benefit from the flexibility of hiring a freelance expert.
  2. b) 専門知識。 More data is available to the present day academicians than in the past. This availability of data has led to newer methods of data analysis. Since many universities are on a ‘hiring freeze’, intramural データサイエンスの専門家 to handle these large volumes of data may not be easily available. If available, these university experts may be swamped with projects. Hiring an external expert will ensure that the projects are smoothly run and produce much-needed publications on time.
  3. c) タイムマネジメントを行う。 ほとんどの学部は時間との戦いで、限られた時間枠の中で質の高い出版物を作り出さなければなりません。「出版するか滅びるか」がマントラであり、滅びるという選択肢はないのです。フリーランスの専門家は、学部とその研究グループが短時間で生産的になるのを助けるかもしれません。
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学術研究の共同化が進む and in recent years; recently, more data sharing initiatives have been started in the US, and also the EU. For instance, in the field of genetics research, in particular with next generation sequencing, analyzing ‘big data’ can help us fight disorders such as cancer, diabetes and neurological disorders. Additionally, analysis of ’big data’ from social media or wearable devices is providing insights into various social, economic, medical and behavioral issues. It is not a surprise that academic researchers are attracted to these ‘big data’. With availability of more data, more research questions can be answered. However, academia might face a shortage of skilled data science experts. A freelance expert can share your burden.


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著者について

アディティは、心と体の相互作用の分野の専門家です。オレゴン大学で人体生理学の博士号を取得後、感情の鈍麻とストレスに関連した生理的変化に焦点を当てた研究を行っています。科学以外では、フードライティング、アート、美術史に興味があります。

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