scholarly journals Teaching Open Science: Published Data and Digital Literacy in Archaeology Classrooms

2018 ◽  
Vol 6 (2) ◽  
pp. 144-156 ◽  
Author(s):  
Katherine Cook ◽  
Canan Çakirlar ◽  
Timothy Goddard ◽  
Robert Carl DeMuth ◽  
Joshua Wells
Keyword(s):  
Digital Literacy ◽  
Open Data ◽  
Skills Training ◽  
The United States ◽  
Open Science ◽  
Data Reuse ◽  
Published Data ◽  
Skill Levels ◽  
And Training ◽  
Different Levels

ABSTRACTDigital literacy has been cited as one of the primary challenges to ensuring data reuse and increasing the value placed on open science. Incorporating published data into classrooms and training is at the core of tackling this issue. This article presents case studies in teaching with different published data platforms, in three different countries (the Netherlands, Canada, and the United States), to students at different levels and with differing skill levels. In outlining their approaches, successes, and failures in teaching with open data, it is argued that collaboration with data publishers is critical to improving data reuse and education. Moreover, increased opportunities for digital skills training and scaffolding across program curriculum are necessary for managing the learning curve and teaching students the values of open science.

scholarly journals Data trajectories: tracking reuse of published data for transitive credit attribution

2016 ◽  
Vol 11 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Paolo Missier
Keyword(s):  
Data Model ◽  
Open Data ◽  
Original Data ◽  
Open Science ◽  
Data Reuse ◽  
Published Data ◽  
Data Sets ◽  
In The Wild ◽  
Context Data ◽  
Direct Measures

The ability to measure the use and impact of published data sets is key to the success of the open data/open science paradigm. A direct measure of impact would require tracking data (re)use in the wild, which is difficult to achieve. This is therefore commonly replaced by simpler metrics based on data download and citation counts. In this paper we describe a scenario where it is possible to track the trajectory of a dataset after its publication, and show how this enables the design of accurate models for ascribing credit to data originators. A Data Trajectory (DT) is a graph that encodes knowledge of how, by whom, and in which context data has been re-used, possibly after several generations. We provide a theoretical model of DTs that is grounded in the W3C PROV data model for provenance, and we show how DTs can be used to automatically propagate a fraction of the credit associated with transitively derived datasets, back to original data contributors. We also show this model of transitive credit in action by means of a Data Reuse Simulator. In the longer term, our ultimate hope is that credit models based on direct measures of data reuse will provide further incentives to data publication. We conclude by outlining a research agenda to address the hard questions of creating, collecting, and using DTs systematically across a large number of data reuse instances in the wild.

scholarly journals Organising RDM and Open Science Services

2019 ◽  
Vol 14 (1) ◽  
pp. 180-193
Author(s):  
Anne Sunikka
Keyword(s):  
Open Data ◽  
Open Science ◽  
Open Access Publishing ◽  
Research Needs ◽  
Ministry Of Education ◽  
Training Material ◽  
Research Data Management ◽  
Changing Roles ◽  
Academic Personnel ◽  
And Training

This paper describes how the Finnish Ministry of Education and Culture launched an initiative on research data management and open data, open access publishing, and open and collaborative ways of working in 2014. Most of the universities and research institutions took part in the collaborative initiative building new tools and training material for the Finnish research needs. Measures taken by one university, Aalto University, are described in detail and analysed, and compared with the activities taking place in other universities. The focus of this paper is in the changing roles of experts at Aalto University, and organisational transformation that offers possibilities to serve academic personnel better. Various ways of building collaboration and arranging services are described, and their benefits and drawbacks are discussed.

scholarly journals From the Court to the Classroom: Judges’ Work in International Judicial Education

2018 ◽  
Author(s):  
Toby S. Goldbach
Keyword(s):  
Rule Of Law ◽  
Skills Training ◽  
The United States ◽  
Education And Training ◽  
The Rule Of Law ◽  
Legal Norms ◽  
Judicial Education ◽  
And Training ◽  
Scholarly Attention ◽  
The Way

49 Cornell International Law Journal 618 (2016).This Article explores international judicial education and training, which are commonly associated with rule of law initiatives and development projects. Judicial education programs address everything from leadership competencies and substantive review of human rights legislation to client service and communication, skills training on docket management software, and alternative dispute resolution. Over the last twenty years, judicial education in support of the rule of law has become big business both in the United States and internationally. The World Bank alone spends approximately U.S. $24 million per year for funded projects primarily attending to improving court performance. And yet, the specifics of judicial education remains unknown in terms of its place in the industry of rule of law initiatives, the number of judges who act as educators, and the mechanisms that secure their participation. This Article focuses on the judges’ experiences; in particular, the judges of the Supreme Court of Israel who were instrumental in establishing the International Organization of Judicial Training.Lawyers, development practitioners, justice experts, and government officials participate in training judges. Less well known is the extent to which judges themselves interact internationally as learners, educators, and directors of training institutes. While much scholarly attention has been paid to finding a global juristocracy in constitutional law, scholars have overlooked the role that judges play in the transnational movement of ideas about court structure, legal procedure, case management, and court administration. Similarly, scholarship examines the way legal norms circulate, the source of institutional change, and the way “transnational legal processes” increase the role of courts within national legal systems. There is little scholarly attention, however, to judges as actors in these transnational processes. This Article situates judicial education and training within the context of judicial functions as an example of judicial involvement in non-caserelated law reform. This Article challenges the instrumental connection between judicial education and the rule of law, arguing that international judicial education became a solution at the same time that the problem— a rule of law deficit— was being identified. This Article also explores whether international judicial education can stand as an instantiation of a global judicial dialogue. Judges have immersed themselves in foreign relations. They are, however, less strategic in pushing their ideological agenda than literature about judges and politics would suggest. This Article argues that judges experience politics as a series of partial connections, which resemble most legal actors’ engagement with the personal and the political.

scholarly journals Data reuse and the open data citation advantage

2013 ◽  
Author(s):  
Heather Piwowar ◽  
Todd J Vision
Keyword(s):  
Gene Expression ◽  
Microarray Data ◽  
Citation Rate ◽  
Open Data ◽  
Data Reuse ◽  
Third Party ◽  
Published Data ◽  
Gene Expression Microarray ◽  
Expression Microarray ◽  
Gene Expression Microarray Data

BACKGROUND: Attribution to the original contributor upon reuse of published data is important both as a reward for data creators and to document the provenance of research findings. Previous studies have found that papers with publicly available datasets receive a higher number of citations than similar studies without available data. However, few previous analyses have had the statistical power to control for the many variables known to predict citation rate, which has led to uncertain estimates of the “citation boost”. Furthermore, little is known about patterns in data reuse over time and across datasets. METHOD AND RESULTS: Here, we look at citation rates while controlling for many known citation predictors, and investigate the variability of data reuse. In a multivariate regression on 10,555 studies that created gene expression microarray data, we found that studies that made data available in a public repository received 9% (95% confidence interval: 5% to 13%) more citations than similar studies for which the data was not made available. Date of publication, journal impact factor, open access status, number of authors, first and last author publication history, corresponding author country, institution citation history, and study topic were included as covariates. The citation boost varied with date of dataset deposition: a citation boost was most clear for papers published in 2004 and 2005, at about 30%. Authors published most papers using their own datasets within two years of their first publication on the dataset, whereas data reuse papers published by third-party investigators continued to accumulate for at least six years. To study patterns of data reuse directly, we compiled 9,724 instances of third party data reuse via mention of GEO or ArrayExpress accession numbers in the full text of papers. The level of third-party data use was high: for 100 datasets deposited in year 0, we estimated that 40 papers in PubMed reused a dataset by year 2, 100 by year 4, and more than 150 data reuse papers had been published by year 5. Data reuse was distributed across a broad base of datasets: a very conservative estimate found that 20% of the datasets deposited between 2003 and 2007 had been reused at least once by third parties. CONCLUSION: After accounting for other factors affecting citation rate, we find a robust citation benefit from open data, although a smaller one than previously reported. We conclude there is a direct effect of third-party data reuse that persists for years beyond the time when researchers have published most of the papers reusing their own data. Other factors that may also contribute to the citation boost are considered. We further conclude that, at least for gene expression microarray data, a substantial fraction of archived datasets are reused, and that the intensity of dataset reuse has been steadily increasing since 2003.

scholarly journals Data reuse and the open data citation advantage

2013 ◽  
Author(s):  
Heather Piwowar ◽  
Todd J Vision
Keyword(s):  
Gene Expression ◽  
Microarray Data ◽  
Citation Rate ◽  
Open Data ◽  
Data Reuse ◽  
Third Party ◽  
Published Data ◽  
Gene Expression Microarray ◽  
Expression Microarray ◽  
Gene Expression Microarray Data

BACKGROUND: Attribution to the original contributor upon reuse of published data is important both as a reward for data creators and to document the provenance of research findings. Previous studies have found that papers with publicly available datasets receive a higher number of citations than similar studies without available data. However, few previous analyses have had the statistical power to control for the many variables known to predict citation rate, which has led to uncertain estimates of the “citation boost”. Furthermore, little is known about patterns in data reuse over time and across datasets. METHOD AND RESULTS: Here, we look at citation rates while controlling for many known citation predictors, and investigate the variability of data reuse. In a multivariate regression on 10,555 studies that created gene expression microarray data, we found that studies that made data available in a public repository received 9% (95% confidence interval: 5% to 13%) more citations than similar studies for which the data was not made available. Date of publication, journal impact factor, open access status, number of authors, first and last author publication history, corresponding author country, institution citation history, and study topic were included as covariates. The citation boost varied with date of dataset deposition: a citation boost was most clear for papers published in 2004 and 2005, at about 30%. Authors published most papers using their own datasets within two years of their first publication on the dataset, whereas data reuse papers published by third-party investigators continued to accumulate for at least six years. To study patterns of data reuse directly, we compiled 9,724 instances of third party data reuse via mention of GEO or ArrayExpress accession numbers in the full text of papers. The level of third-party data use was high: for 100 datasets deposited in year 0, we estimated that 40 papers in PubMed reused a dataset by year 2, 100 by year 4, and more than 150 data reuse papers had been published by year 5. Data reuse was distributed across a broad base of datasets: a very conservative estimate found that 20% of the datasets deposited between 2003 and 2007 had been reused at least once by third parties. CONCLUSION: After accounting for other factors affecting citation rate, we find a robust citation benefit from open data, although a smaller one than previously reported. We conclude there is a direct effect of third-party data reuse that persists for years beyond the time when researchers have published most of the papers reusing their own data. Other factors that may also contribute to the citation boost are considered. We further conclude that, at least for gene expression microarray data, a substantial fraction of archived datasets are reused, and that the intensity of dataset reuse has been steadily increasing since 2003.

scholarly journals African–Caribbean Cancer Consortium Scientific and Training Conference 2017rence 2017 Meeting Report

2019 ◽  
Vol 26 (6) ◽  
Author(s):  
C. Ragin ◽  
J. S. Oliver ◽  
D. N. Cabral ◽  
M. Harlemon ◽  
D. Louden ◽  
...  
Keyword(s):  
Skills Training ◽  
The United States ◽  
Cancer Surveillance ◽  
Meeting Report ◽  
Community Members ◽  
Public Health Professionals ◽  
African Caribbean ◽  
The Caribbean ◽  
And Training ◽  
Sixth International

The sixth International African–Caribbean Cancer Consortium (AC3) Conference was held 6–9 October 2017 in Miami, Florida, U.S.A. The conference was open to all researchers, trainees, clinical and public health professionals, and community members, and served as an international hub for the United States, the Caribbean, and Africa. Sessions included AC3 collaboration meetings, cancer surveillance and research skills training workshops, and a community cancer prevention conference.

scholarly journals Organizing Young Workers Under Precarious Conditions: What Hinders or Facilitates Union Success

2018 ◽  
Vol 45 (4) ◽  
pp. 420-450 ◽  
Author(s):  
Melanie Simms ◽  
Dennis Eversberg ◽  
Camille Dupuy ◽  
Lena Hipp
Keyword(s):  
Working Hours ◽  
Skills Training ◽  
The United States ◽  
Coalition Building ◽  
Existing Structures ◽  
The United Kingdom ◽  
Training Quality ◽  
Training Activities ◽  
Training Demands ◽  
And Training

Under what conditions do young precarious workers join unions? Based on case studies from France, Germany, the United Kingdom, and the United States, the authors identify targeted campaigns, coalition building, membership activism, and training activities as innovative organizing approaches. In addition to traditional issues such as wages and training quality, these approaches also featured issues specific to precarious workers, including skills training, demands for minimum working hours, and specific support in insecure employment situations. Organizing success is influenced by bargaining structures, occupational identity, labor market conditions, and support by union leaders and members. Innovative organizing tends to happen when unions combine new approaches with existing structures.

scholarly journals Applying a Community Informatics Approach as Part of Rehabilitation in US Prisons

2011 ◽  
Vol 6 (3) ◽  
Author(s):  
Lassana Magassa
Keyword(s):  
Digital Divide ◽  
Digital Literacy ◽  
Information Society ◽  
The United States ◽  
United States Government ◽  
Prison Inmates ◽  
Socioeconomic System ◽  
States Government ◽  
Vital Component ◽  
And Training

The United States Government has acknowledged that digital literacy is a vital component of 21st century education and civic engagement. As such efforts are being made to draw in segments of the population that are negatively affected by the digital divide. Not included in these efforts is a community of individuals, most of who have the lowest literacy rates and come from the lowest income strata in society—prison inmates. Despite a few scattered attempts, these individuals have virtually no access to resources and training that would create the condition by which when released they will be able to complete commonplace tasks that depend on an assortment of digital technologies. Discussions around access are often confronted with scepticism by prison administration and citizens alike. This paper uses the information obtained about National and Washington state specific prisons to describe the landscape and the importance of preparing incarcerated individuals to confront an information society. Finally, using the Access Rainbow, the paper brings forth obstacles related to introducing a level of access and training that will prepare inmates to be productive participants in a technological based socioeconomic system after release from prison.

scholarly journals Open Science in Kenya: Where are we?

2021 ◽  
Author(s):  
Kennedy Mwangi ◽  
Ben Mainye ◽  
Daniel Ouso ◽  
Esoh Kevin ◽  
Angela Muraya ◽  
...  
Keyword(s):  
Open Access ◽  
Open Data ◽  
Scientific Research ◽  
Modern Science ◽  
Open Science ◽  
The State ◽  
Science Practices ◽  
Access Cost ◽  
State Of Affairs ◽  
And Training

According to the United Nations Educational, Scientific, and Cultural Organization (UNESCO), Open Science is the movement to make scientific research and data accessible to all. It has great potential for advancing science. At its core, it includes (but is not limited to) open access, open data, and open research. Some of the associated advantages are promoting collaboration, sharing, and reproducibility in research, and preventing the reinvention of the wheel, thus saving resources. As research becomes more globalized and its output grows exponentially, especially in data, the need for open scientific research practices is more evident — the future of modern science. This has resulted in a concerted global interest in open science uptake. Even so, barriers still exist. The formal training curriculum in most, if not all, universities in Kenya does not equip students with the knowledge and tools to subsequently practice open science in their research. Therefore, to work openly and collaboratively, there is a need for awareness and training in the use of open science tools. These have been neglected, especially in most developing countries, and remain barriers to the cause. Moreover, there is scanty research on the state of affairs regarding the practice and/or adoption of open science. Thus, we developed, through the OpenScienceKE framework, a model to narrow the gap. A sensitize-train-hack-collaborate model was applied in Nairobi, the economic and administrative capital of Kenya. Using the model, we sensitized through seminars, trained on the use of tools through workshops, applied the skills learned in training through hackathons to collaboratively answer the question on the state of open science in Kenya. While the former parts of the model had 20 - 50 participants, the latter part mainly involved participants with a bioinformatics background, leveraging their advanced computational skills. This model resulted in an open resource that researchers can use to publish as open access cost-effectively. Moreover, we observed a growing interest in open science practices in Kenya through literature search and data mining, and that lack of awareness and skills may still hinder the adoption and practice of open science. Furthermore, at the time of the analyses, we surprisingly found that out of the 20,069 papers downloaded from BioRXiv, only 18 had Kenyan authors, a majority of which are international (16) collaborations. This may suggest poor uptake of the use of preprints among Kenyan researchers. The findings in this study highlight the state of open science in Kenya and the challenges facing its adoption and practice while bringing forth possible areas for primary consideration in the campaign towards open science. It also proposes a model (sensitize-train-hack-collaborate model) that may be adopted by researchers, funders, and other proponents of open science to address some of the challenges faced in promoting its adoption in Kenya.

scholarly journals Data Reuse and the Social Capital of Open Science

2016 ◽  
Author(s):  
Bradly Alicea
Keyword(s):  
Game Theory ◽  
Social Capital ◽  
Data Sharing ◽  
Open Data ◽  
Open Science ◽  
Payoff Matrix ◽  
Reciprocal Relationship ◽  
Data Reuse ◽  
Data Set ◽  
Shared Data

ABSTRACTParticipation in open data initiatives require two semi-independent actions: the sharing of data produced by a researcher or group, and a consumer of shared data. Consumers of shared data range from people interested in validating the results of a given study to people who actively transform the available data. These data transformers are of particular interest because they add value to the shared data set through the discovery of new relationships and information which can in turn be shared with the same community. The complex and often reciprocal relationship between producers and consumers can be better understood using game theory, namely by using three variations of the Prisoners’ Dilemma (PD): a classical PD payoff matrix, a simulation of the PD n-person iterative model that tests three hypotheses, and an Ideological Game Theory (IGT) model used to formulate how sharing strategies might be implemented in a specific institutional culture. To motivate these analyses, data sharing is presented as a trade-off between economic and social payoffs. This is demonstrated as a series of payoff matrices describing situations ranging from ubiquitous acceptance of Open Science principles to a community standard of complete non-cooperation. Further context is provided through the IGT model, which allows from the modeling of cultural biases and beliefs that influence open science decision-making. A vision for building a CC-BY economy are then discussed using an approach called econosemantics, which complements the treatment of data sharing as a complex system of transactions enabled by social capital.

Sign in / Sign up

Export Citation Format

Share Document