Evidence map›Paper›PMID 36159891›Full record

ArticleEmpirical software engineering2022

Developing research questions in conversation with the literature: operationalization & tool support.

Oscar Díaz, Jeremías P Contell

Abstract read
In one paragraph

Article in Empirical software engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Oscar DíazONEKIN Research Group, University of the Basque Country (UPV/EHU), San Sebastian, Spain.ORCID 0000-0003-1334-4761
Jeremías P ContellONEKIN Research Group, University of the Basque Country (UPV/EHU), San Sebastian, Spain.ORCID 0000-0002-2041-6674

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Empirical Software Engineering rests on the understanding of practical problems and their solution counterparts. Frequently, solutions are not absolute but relative to the context where the problem is observed. This tends to imply that the solution and the problem unveil gradually together, and hence, researchers are not always in the position to state the research question (RQ) at the onset. Like software engineers when facing blurred requirements, researchers might not be familiar enough with the problem in the early phases of a research to properly scope their RQs (hereafter referred to as RQ Scoping). Here, the literature may play the role of the stakeholders in Agile methods: keeping the focus on the aspects that are essential (vs. accidental) of the RQ. Informed by Inductive Top-Down Theorizing, this article acknowledges RQ Scoping as iterative and incremental, entailing a conversation between the experimental work and literature reviewing. Yet, for literature reviewing to become "Agile" it is not only required to be driven by the RQ but also to have tool support. Tools might bring transparency and traceability, both factors especially welcome in a scenario characterized by testing (is my RQ relevant?) and adjustment (how can I make my RQ relevant?). Specifically, the advent of the RQ in close relationship with the literature advises for "Agile" literature reviewing to be conducted at the place where the literature is naturally kept: the Reference Management System (e.g., Mendeley). This article introduces the theoretical underpinnings, design principles, proof of concept and evaluation for FRAMEndeley, a Mendeley-integrated utility for RQ Scoping.

Indexed as

Inductive Top-Down TheorizingLiterature reviewReference management systemsResearch question

Identifiers

PMID36159891
PMCPMC9486795

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.