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The reuse of public datasets in the life sciences: potential risks and rewards.

ABSTRACT: The 'big data' revolution has enabled novel types of analyses in the life sciences, facilitated by public sharing and reuse of datasets. Here, we review the prodigious potential of reusing publicly available datasets and the associated challenges, limitations and risks. Possible solutions to issues and research integrity considerations are also discussed. Due to the prominence, abundance and wide distribution of sequencing data, we focus on the reuse of publicly available sequence datasets. We define 'successful reuse' as the use of previously published data to enable novel scientific findings. By using selected examples of successful reuse from different disciplines, we illustrate the enormous potential of the practice, while acknowledging the respective limitations and risks. A checklist to determine the reuse value and potential of a particular dataset is also provided. The open discussion of data reuse and the establishment of this practice as a norm has the potential to benefit all stakeholders in the life sciences.

SUBMITTER: Sielemann K

PROVIDER: S-EPMC7518187 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The reuse of public datasets in the life sciences: potential risks and rewards.

Sielemann Katharina K Hafner Alenka A Pucker Boas B

PeerJ 20200922

The 'big data' revolution has enabled novel types of analyses in the life sciences, facilitated by public sharing and reuse of datasets. Here, we review the prodigious potential of reusing publicly available datasets and the associated challenges, limitations and risks. Possible solutions to issues and research integrity considerations are also discussed. Due to the prominence, abundance and wide distribution of sequencing data, we focus on the reuse of publicly available sequence datasets. We d ...[more]

PMID: 33024631

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Project description:BackgroundThe web has seen an explosion of chemistry and biology related resources in the last 15 years: thousands of scientific journals, databases, wikis, blogs and resources are available with a wide variety of types of information. There is a huge need to aggregate and organise this information. However, the sheer number of resources makes it unrealistic to link them all in a centralised manner. Instead, search engines to find information in those resources flourish, and formal languages like Resource Description Framework and Web Ontology Language are increasingly used to allow linking of resources. A recent development is the use of userscripts to change the appearance of web pages, by on-the-fly modification of the web content. This opens possibilities to aggregate information and computational results from different web resources into the web page of one of those resources.ResultsSeveral userscripts are presented that enrich biology and chemistry related web resources by incorporating or linking to other computational or data sources on the web. The scripts make use of Greasemonkey-like plugins for web browsers and are written in JavaScript. Information from third-party resources are extracted using open Application Programming Interfaces, while common Universal Resource Locator schemes are used to make deep links to related information in that external resource. The userscripts presented here use a variety of techniques and resources, and show the potential of such scripts.ConclusionThis paper discusses a number of userscripts that aggregate information from two or more web resources. Examples are shown that enrich web pages with information from other resources, and show how information from web pages can be used to link to, search, and process information in other resources. Due to the nature of userscripts, scientists are able to select those scripts they find useful on a daily basis, as the scripts run directly in their own web browser rather than on the web server. This flexibility allows the scientists to tune the features of web resources to optimise their productivity.

Project description:ObjectivesSurgeons will face an increasing number of octogenarians with lung cancer potentially curable by surgery. The goal of this study was to evaluate short- and long-term outcomes after lung resection.MethodsWe performed a single-centre study of consecutive patients ≥80 years old, surgically treated for suspected lung cancer between 2009 and 2016. Age, sex, performance status, lung function, surgical approach, type of lung resection, complications, in-hospital and 30- and 90-day deaths and long-term survival were analysed.ResultsTwo hundred and fifty-seven patients were enrolled. The median age was 82 years (range 80-97). One hundred and thirty-four patients were treated by thoracotomy and 123 by video-assisted thoracic surgery [10 (8.1%) converted]. Two hundred and thirty-two underwent lobar resection and 25 underwent sublobar resection. There were no intraoperative deaths and 9 admissions to the intensive therapy unit; 112 (43.6%) patients suffered complications: More complications occurred after lobar versus after sublobar resections [45.7% vs 24% (P = 0.037)] and in those with chronic obstructive pulmonary disease (COPD) [57.4% vs 40% (P = 0.02)]. The 30-day mortality was 3.9% (n = 10) and the 90-day mortality was 6.22% (n = 16). One hundred and sixty-seven patients died during the study period; patients with non-small-cell lung cancer (n = 233) had a median survival of 46.5 months with 67.2% alive at 2 years and 40.8% at 5 years. Pathological stage and R status were independent prognostic factors for survival.ConclusionsSurgery for malignancies in octogenarians is feasible and safe with good long-term outcomes. The risk of postoperative complications, especially in those with COPD, is high but can be minimized with sublobar resection. Postoperative mortality is acceptable, and long-term survival is primarily governed by lung cancer stage. Age is no reason to deny patients surgery for early-stage disease.

Dataset Information

The reuse of public datasets in the life sciences: potential risks and rewards.

Publications

The reuse of public datasets in the life sciences: potential risks and rewards.

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