scholarly journals Peer-Reviewed Open Research Data: Results of a Pilot

2012 ◽  
Vol 7 (2) ◽  
pp. 81-91 ◽  
Author(s):  
Marjan Grootveld ◽  
Jeff Van Egmond

Peer review of publications is at the core of science and primarily seen as instrument for ensuring research quality. However, it is less common to independently value the quality of the underlying data as well. In the light of the ‘data deluge’ it makes sense to extend peer review to the data itself and this way evaluate the degree to which the data are fit for re-use. This paper describes a pilot study at EASY - the electronic archive for (open) research data at our institution. In EASY, researchers can archive their data and add metadata themselves. Devoted to open access and data sharing, at the archive we are interested in further enriching these metadata with peer reviews.As a pilot, we established a workflow where researchers who have downloaded data sets from the archive were asked to review the downloaded data set. This paper describes the details of the pilot including the findings, both quantitative and qualitative. Finally, we discuss issues that need to be solved when such a pilot is turned into a structural peer review functionality for the archiving system.

Publications ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 14
Author(s):  
Eirini Delikoura ◽  
Dimitrios Kouis

Recently significant initiatives have been launched for the dissemination of Open Access as part of the Open Science movement. Nevertheless, two other major pillars of Open Science such as Open Research Data (ORD) and Open Peer Review (OPR) are still in an early stage of development among the communities of researchers and stakeholders. The present study sought to unveil the perceptions of a medical and health sciences community about these issues. Through the investigation of researchers` attitudes, valuable conclusions can be drawn, especially in the field of medicine and health sciences, where an explosive growth of scientific publishing exists. A quantitative survey was conducted based on a structured questionnaire, with 179 valid responses. The participants in the survey agreed with the Open Peer Review principles. However, they ignored basic terms like FAIR (Findable, Accessible, Interoperable, and Reusable) and appeared incentivized to permit the exploitation of their data. Regarding Open Peer Review (OPR), participants expressed their agreement, implying their support for a trustworthy evaluation system. Conclusively, researchers need to receive proper training for both Open Research Data principles and Open Peer Review processes which combined with a reformed evaluation system will enable them to take full advantage of the opportunities that arise from the new scholarly publishing and communication landscape.


2017 ◽  
Vol 19 (2) ◽  
pp. 53-66 ◽  
Author(s):  
Michael Preston-Shoot

Purpose The purpose of this paper is twofold: first, to update the core data set of self-neglect serious case reviews (SCRs) and safeguarding adult reviews (SARs), and accompanying thematic analysis; second, to respond to the critique in the Wood Report of SCRs commissioned by Local Safeguarding Children Boards (LSCBs) by exploring the degree to which the reviews scrutinised here can transform and improve the quality of adult safeguarding practice. Design/methodology/approach Further published reviews are added to the core data set from the websites of Safeguarding Adults Boards (SABs) and from contacts with SAB independent chairs and business managers. Thematic analysis is updated using the four domains employed previously. The findings are then further used to respond to the critique in the Wood Report of SCRs commissioned by LSCBs, with implications discussed for Safeguarding Adult Boards. Findings Thematic analysis within and recommendations from reviews have tended to focus on the micro context, namely, what takes place between individual practitioners, their teams and adults who self-neglect. This level of analysis enables an understanding of local geography. However, there are other wider systems that impact on and influence this work. If review findings and recommendations are to fully answer the question “why”, systemic analysis should appreciate the influence of national geography. Review findings and recommendations may also be used to contest the critique of reviews, namely, that they fail to engage practitioners, are insufficiently systemic and of variable quality, and generate repetitive findings from which lessons are not learned. Research limitations/implications There is still no national database of reviews commissioned by SABs so the data set reported here might be incomplete. The Care Act 2014 does not require publication of reports but only a summary of findings and recommendations in SAB annual reports. This makes learning for service improvement challenging. Reading the reviews reported here against the strands in the critique of SCRs enables conclusions to be reached about their potential to transform adult safeguarding policy and practice. Practical implications Answering the question “why” is a significant challenge for SARs. Different approaches have been recommended, some rooted in systems theory. The critique of SCRs challenges those now engaged in SARs to reflect on how transformational change can be achieved to improve the quality of adult safeguarding policy and practice. Originality/value The paper extends the thematic analysis of available reviews that focus on work with adults who self-neglect, further building on the evidence base for practice. The paper also contributes new perspectives to the process of conducting SARs by using the analysis of themes and recommendations within this data set to evaluate the critique that reviews are insufficiently systemic, fail to engage those involved in reviewed cases and in their repetitive conclusions demonstrate that lessons are not being learned.


2011 ◽  
pp. 24-32 ◽  
Author(s):  
Nicoleta Rogovschi ◽  
Mustapha Lebbah ◽  
Younès Bennani

Most traditional clustering algorithms are limited to handle data sets that contain either continuous or categorical variables. However data sets with mixed types of variables are commonly used in data mining field. In this paper we introduce a weighted self-organizing map for clustering, analysis and visualization mixed data (continuous/binary). The learning of weights and prototypes is done in a simultaneous manner assuring an optimized data clustering. More variables has a high weight, more the clustering algorithm will take into account the informations transmitted by these variables. The learning of these topological maps is combined with a weighting process of different variables by computing weights which influence the quality of clustering. We illustrate the power of this method with data sets taken from a public data set repository: a handwritten digit data set, Zoo data set and other three mixed data sets. The results show a good quality of the topological ordering and homogenous clustering.


2021 ◽  
Vol 27 (3) ◽  
pp. 8-34
Author(s):  
Tatyana Cherkashina

The article presents the experience of converting non-targeted administrative data into research data, using as an example data on the income and property of deputies from local legislative bodies of the Russian Federation for 2019, collected as part of anticorruption operations. This particular empirical fragment was selected for the pilot study of administrative data, which includes assessing the possibility of integrating scattered fragments of information into a single database, assessing quality of data and their relevance for solving research problems, particularly analysis of high-income strata and the apparent trends towards individualization of private property. The system of indicators for assessing data quality includes their timeliness, availability, interpretability, reliability, comparability, coherence, errors of representation and measurement, and relevance. In the case of the data set in question, measurement errors are more common than representation errors. Overall the article emphasizes the notion that introducing new non-target data into circulation requires their preliminary testing, while data quality assessment becomes distributed both in time and between different subjects. The transition from created data to «obtained» data shifts the functions of evaluating its quality from the researcher-creator to the researcheruser. And though in this case data quality is in part ensured by the legal support for their production, the transformation of administrative data into research data involves assessing a variety of quality measurements — from availability to uniformity and accuracy.


Author(s):  
Liah Shonhe

The main focus of the study was to explore the practices of open data sharing in the agricultural sector, including establishing the research outputs concerning open data in agriculture. The study adopted a desktop research methodology based on literature review and bibliographic data from WoS database. Bibliometric indicators discussed include yearly productivity, most prolific authors, and enhanced countries. Study findings revealed that research activity in the field of agriculture and open access is very low. There were 36 OA articles and only 6 publications had an open data badge. Most researchers do not yet embrace the need to openly publish their data set despite the availability of numerous open data repositories. Unfortunately, most African countries are still lagging behind in management of agricultural open data. The study therefore recommends that researchers should publish their research data sets as OA. African countries need to put more efforts in establishing open data repositories and implementing the necessary policies to facilitate OA.


2020 ◽  
pp. 016555152096104
Author(s):  
Alfonso Quarati ◽  
Juliana E Raffaghelli

Open research data (ORD) have been considered a driver of scientific transparency. However, data friction, as the phenomenon of data underutilisation for several causes, has also been pointed out. A factor often called into question for ORD low usage is the quality of the ORD and associated metadata. This work aims to illustrate the use of ORD, published by the Figshare scientific repository, concerning their scientific discipline, their type and compared with the quality of their metadata. Considering all the Figshare resources and carrying out a programmatic quality assessment of their metadata, our analysis highlighted two aspects. First, irrespective of the scientific domain considered, most ORD are under-used, but with exceptional cases which concentrate most researchers’ attention. Second, there was no evidence that the use of ORD is associated with good metadata publishing practices. These two findings opened to a reflection about the potential causes of such data friction.


2017 ◽  
Vol 6 (3) ◽  
pp. 71 ◽  
Author(s):  
Claudio Parente ◽  
Massimiliano Pepe

The purpose of this paper is to investigate the impact of weights in pan-sharpening methods applied to satellite images. Indeed, different data sets of weights have been considered and compared in the IHS and Brovey methods. The first dataset contains the same weight for each band while the second takes in account the weighs obtained by spectral radiance response; these two data sets are most common in pan-sharpening application. The third data set is resulting by a new method. It consists to compute the inertial moment of first order of each band taking in account the spectral response. For testing the impact of the weights of the different data sets, WorlView-3 satellite images have been considered. In particular, two different scenes (the first in urban landscape, the latter in rural landscape) have been investigated. The quality of pan-sharpened images has been analysed by three different quality indexes: Root mean square error (RMSE), Relative average spectral error (RASE) and Erreur Relative Global Adimensionnelle de Synthèse (ERGAS).


Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 175 ◽  
Author(s):  
Tibor Koltay

This paper focuses on the characteristics of research data quality, and aims to cover the most important issues related to it, giving particular attention to its attributes and to data governance. The corporate word’s considerable interest in the quality of data is obvious in several thoughts and issues reported in business-related publications, even if there are apparent differences between values and approaches to data in corporate and in academic (research) environments. The paper also takes into consideration that addressing data quality would be unimaginable without considering big data.


2019 ◽  
Vol 32 (1) ◽  
pp. 2-25 ◽  
Author(s):  
James Guthrie ◽  
Lee D. Parker ◽  
John Dumay ◽  
Markus J. Milne

Purpose The purpose of this paper is to reflect upon the focus and changing nature of measuring academic accounting research quality. The paper addresses contemporary changes in academic publishing, metrics for determining research quality and the possible impacts on accounting scholars. These are considered in relation to the core values of interdisciplinary accounting research ‒ that is, the pursuit of novel, rigorous, significant and authentic research motivated by a passion for scholarship, curiosity and solving wicked problems. The impact of changing journal rankings and research citation metrics on the traditional and highly valued role of the accounting academic is further considered. In this setting, the paper also provides a summary of the journal’s activities for 2018, and in the future. Design/methodology/approach Drawing on contemporary data sets, the paper illustrates the increasingly diverse and confusing array of “evidence” brought to bear on the question of the relative quality of accounting research. Commercial products used to rate and rank journals, and judge the academic impact of individual scholars and their papers not only offer insight and visibility, but also have the potential to misinform scholars and their assessors. Findings In the move from simple journal ranking lists to big data and citations, and increasingly to concerns with impact and engagement, the authors identify several challenges facing academics and administrators alike. The individual academic and his or her contribution to scholarship are increasingly marginalised in the name of discipline, faculty and institutional performance. A growing university performance management culture within, for example, the UK and Australasia, has reached a stage in the past decade where publication and citation metrics are driving allocations of travel grants, research grants, promotions and appointments. With an expanded range of available metrics and products to judge their worth, or have it judged for them, scholars need to be increasingly informed of the nuanced or not-so-nuanced uses to which these measurement systems will be put. Narrow, restricted and opaque peer-based sources such as journal ranking lists are now being challenged by more transparent citation-based sources. Practical implications The issues addressed in this commentary offer a critical understanding of contemporary metrics and measurement in determining the quality of interdisciplinary accounting research. Scholars are urged to reflect upon the challenges they face in a rapidly moving context. Individuals are increasingly under pressure to seek out preferred publication outlets, developing and curating a personal citation profile. Yet such extrinsic outcomes may come at the cost of the core values that motivate the interdisciplinary scholar and research. Originality/value This paper provides a forward-looking focus on the critical role of academics in interdisciplinary accounting research.


2005 ◽  
Vol 5 (7) ◽  
pp. 1835-1841 ◽  
Author(s):  
S. Noël ◽  
M. Buchwitz ◽  
H. Bovensmann ◽  
J. P. Burrows

Abstract. A first validation of water vapour total column amounts derived from measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) in the visible spectral region has been performed. For this purpose, SCIAMACHY water vapour data have been determined for the year 2003 using an extended version of the Differential Optical Absorption Spectroscopy (DOAS) method, called Air Mass Corrected (AMC-DOAS). The SCIAMACHY results are compared with corresponding water vapour measurements by the Special Sensor Microwave Imager (SSM/I) and with model data from the European Centre for Medium-Range Weather Forecasts (ECMWF). In confirmation of previous results it could be shown that SCIAMACHY derived water vapour columns are typically slightly lower than both SSM/I and ECMWF data, especially over ocean areas. However, these deviations are much smaller than the observed scatter of the data which is caused by the different temporal and spatial sampling and resolution of the data sets. For example, the overall difference with ECMWF data is only -0.05 g/cm2 whereas the typical scatter is in the order of 0.5 g/cm2. Both values show almost no variation over the year. In addition, first monthly means of SCIAMACHY water vapour data have been computed. The quality of these monthly means is currently limited by the availability of calibrated SCIAMACHY spectra. Nevertheless, first comparisons with ECMWF data show that SCIAMACHY (and similar instruments) are able to provide a new independent global water vapour data set.


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