Evidence map›Paper›PMID 36628121›Full record

ArticleSynthetic biology (Oxford, England)2023

An economy of details: standards and data reusability.

Ana Delgado

Open access · goldAbstract read
In one paragraph

Article in Synthetic biology (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 51% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Ana DelgadoTIK Centre for Technology, Innovation and Culture, University of Oslo, Oslo, Norway.ORCID https://orcid.org/0000-0001-7569-3137
University of Oslo · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reusability has been a key issue since the origins of the parts-based approach to synthetic biology. Starting with the BioBrick™ standard part, multiple efforts have aimed to make biology more exchangeable. The reusability of parts and other deoxyribonucleic acid-based data has proven over time to be challenging, however. Drawing on a series of qualitative interviews and an international workshop, this article explores the challenges of reusability in real laboratory practice. It shows particular ways that standards are experienced as presenting shortcomings for capturing the kinds of contextual information crucial for scientists to be able to reuse biological parts and data. I argue that researchers in specific laboratories develop a sense of how much circumstantial detail they need to share for others to be able to make sense of their data and possibly reuse it. When choosing particular reporting formats, recharacterizing data to gain closer knowledge or requesting additional information, researchers enact an 'economy of details'. The farther apart two laboratories are in disciplinary, epistemological, technical and geographical terms, the more detailed information needs to be captured for data to be reusable across contexts. In synthetic biology, disciplinary distance between computing science and engineering researchers and experimentalist biologists is reflected in diverging views on standards: what kind of information should be included to enable reusability, what kind of information can be captured by standards at all and how they may serve to produce and circulate knowledge. I argue that such interdisciplinary tensions lie at the core of difficulties in setting standards in synthetic biology.

Indexed as

dataexperimentinfrastructuresreproducibilityreusabilitystandards

Identifiers

PMID36628121
PMCPMC9817096
OpenAlexW4311191938

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.