Data-Intensive Science and Research Integrity

被引：11

作者：

Resnik, David B. ^{[1
]}

Elliott, Kevin C. ^{[2
,3
,4
]}

Soranno, Patricia A. ^{[3
]}

Smith, Elise M. ^{[1
]}

机构：

[1] NIEHS, NIH, 111 Alexander Dr, Res Triangle Pk, NC 27709 USA

[2] Michigan State Univ, Lyman Briggs Coll, E Lansing, MI 48824 USA

[3] Michigan State Univ, Dept Fisheries & Wildlife, E Lansing, MI 48824 USA

[4] Michigan State Univ, Dept Philosophy, E Lansing, MI 48824 USA

来源：

ACCOUNTABILITY IN RESEARCH-ETHICS INTEGRITY AND POLICY | 2017年 / 24卷 / 06期

基金：

美国国家卫生研究院; 美国国家科学基金会;

关键词：

Data-intensive science; deception; education; ethics; misconduct; research integrity; transparency; MISCONDUCT; POLICIES;

D O I：

10.1080/08989621.2017.1327813

中图分类号：

R-052 [医学伦理学];

学科分类号：

0101 ; 120402 ;

摘要：

In this commentary, we consider questions related to research integrity in data-intensive science and argue that there is no need to create a distinct category of misconduct that applies to deception related to processing, analyzing, or interpreting data. The best way to promote integrity in data-intensive science is to maintain a firm commitment to epistemological and ethical values, such as honesty, openness, transparency, and objectivity, which apply to all types of research, and to promote education, policy development, and scholarly debate concerning appropriate uses of statistics.

引用

页码：344 / 358

页数：15

共 64 条

[1]

[Anonymous], ETH GUID STAT PRACT

[2]

[Anonymous], 2011, Social network analysis

[3]

[Anonymous], ETHICAL DATA MINING

[4]

[Anonymous], 2009, Microsoft Research

[5]

[Anonymous], TOP 10 LARG DAT WORL

[6]

[Anonymous], 1994, The bell curve: intelligence and class structure in American life

[7]

[Anonymous], 2013, CLIM CHANG 2013 PHYS, DOI DOI 10.1017/CBO9781107415324

[8]

[Anonymous], 2000, Federal Register, V65, P76260

[9]

[Anonymous], SCI INTEGRITY

[10]

[Anonymous], BETRAYERS OF TRUTH

← 1 2 3 4 5 6 7 →