ROLE OF HARVARD DATAVERSE PROJECT IN RESEARCH DATA MANAGEMENT SERVICES

Purpose: To simplify working with and sharing research data, researchers want infrastructures that provide the highest level of accessibility, stability, and reliability. The Harvard Dataverse Project (HDP) (https://dataverse.org/) is compiling a growing list of such infrastructures. In this regard, the objective of this paper is to provide an overview through an analysis of the activities of the Dataverse website in managing research data. Design/ Methodology/ Approach: The study examines the statistics systems and other critical resources concerning upload and use the dataverse/ datasets/ files upto October 2022. This includes the creation of dataverse, category of dataverse, uploaded total datasets, file downloads trend, publication of dataverse or datasets, most approachable subject to share and browse data, the most recommended file type of research data and access level of research data. The basic resources include top metadata sources and data citation standards of dataverse project. Findings: It is noted that behaviours associated with structured study outcomes are more evident in developed countries as opposed to developing countries according to top author affiliation which is from the USA. The findings also show that research data in Medicine, Health, and Life Sciences is more uploaded and structured, whereas data in Social Sciences is more browsed and structured. Overall, the generation of dataverses, datasets, files, their downloads, and publication dataset is on the rise. The maximum contribution of data developers is found as Master, Daniel M. and Stager, Lawrence E whereas research project category and data and image file format are seen as highly used to organize data. On the dataverse website, good citation standards are being noticed, as well as the fact that 97 percent of data are available to reuse because contributors waive their copyright licences under CC0. Originality/ Value: This study presented an overall picture of the growing research data practices throughout the investigation on the Harvard Dataverse platform. The research proposed best practices focused on RDM operations to improve the amount of Research Data activities

Evaluation of axial length measurements obtained using three different techniques- applanation A-scan, immersion A-scan and optical biometer

Background: To compare measurements of axial length obtained with manual A-scan, immersion A-scan and optical biometer and assess the accuracy of different techniques of intraocular lens power calculation. Methods: This was a prospective randomized study done in 90 patients over a period extending from November 2019 to October 2020 in the upgraded department of ophthalmology, Government Medical College Jammu. Intraocular lens power was calculated by measuring axial length by three different techniques and further the accuracy of the axial length values obtained were compared. Results: In this study, mean axial length measured by applanation A-scan was 22.86±0.85 mm which ranged from 20.99-24.6 mm and axial length measured by immersion technique ranged from 21.5-24.9 mm with a mean AL of 22.92±0.85 mm. AL measured by non-contact method ranged from 20-25.08 mm with a mean AL of 23.1±0.93 mm. There was a statistically significant difference between all the three techniques regarding the measured AL (p=0.0004). Conclusions: This study concludes that the optical biometry has greater accuracy than ultrasound biometry including applanation and immersion A-scan

Making research data discoverable: an outreach activity of Datacite

Objective The enormous growth in research data generated today has highlighted the value of data management (RDM) to make research FAIR (Findable, Accessible, Interconnected and Reusable). Appropriate data instructs researchers to use and reuse that data within appropriate citations and attribute it to the author. And Data citation refers to the process of presenting a reference to data in the same way as a bibliographic reference to printed resources is regularly provided by researchers. In this regard, the objective of this paper is to investigate the activities of the Datacite website in managing research data. Methodology The study approached the Datacite website, a non-profit organization that provides analysis with persistent identifiers (DOIs). The research examines the Statistics systems and other critical resources. Registrations by the Collective group and most involved repositories are included in the statistical approaches. The basic resources include top executives, OAI-PMH, DataCite Public Roadmap, DataCite Commons, DataCite/ORCID Auto-update and Service Providers. The outcomes were analysed by MS Excel. Results It is noted that there were 293 members of the registry from different countries. The USA was at the top of the 137 members according to registration, while at least one was located in India, Finland, Spain, etc. Germany was listed as the top member and most of the repository holding companies. Datafirst is the only server found in an Indian context. DataCite Commons found as a discovery tool which allows simple searches by works, individuals and organisations, while providing users with a detailed overview of the relationships between the entities in the research setting. Using the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH), the DataCite service exposes metadata stored in the DataCite Metadata Store (MDS). Datacite Auto-update unambiguously categorises researchers and provides tools to automate the link between researchers and their creative work

Challenges of Nurturing the Gifted and Talented in Developing Countries: Experiences from Rural and Urban India (NIAS/SSc/EDU/U/PR/18/2019)

Gifted children are those children with exceptional ability that place them in the top 3% of the peer group. The NIAS-EGT addresses the gifted and talented children in the age group 0-18 years. NIAS-EGT has developed multiple protocols of identification and mentors of gifted children in rural, urban and tribal population of India. The report documents the challenges and lessons learnt that will be relevant for developing countries

Management of Secondary Glaucoma, a Rising Challenge

Secondary glaucoma has increased exponentially in recent times. This is partially due to the increase in complex eye surgeries like corneal transplantation and vitreoretinal surgery and partly due to the increase in life style related diseases like diabetes causing an increase in the prevalence of neovascular glaucoma. The other leading causes of secondary glaucoma are post-trauma, post-cataract surgery, and lens-induced glaucoma. Secondary glaucoma is an important cause of visual morbidity. The management of this complex glaucoma is difficult as they are mostly intractable and do not respond to anti-glaucoma medications. Many patients who are not managed by medical management may require surgical intervention along with vigilant control of their primary pathology. This course would address the stepwise approach to the management of these glaucomas and the tips and tricks to tackle the nuances during management. This chapter would specifically address the management of neovascular glaucoma, Post-PK glaucoma, lens-induced glaucoma, traumatic glaucoma, and uveitic glaucoma

Preserving Global Research Data: Role and Status of Re3data in RDM

Purpose: Considering that scientific data is being increasingly renowned as an important raw material for current and future technological advances, many research collaborators have joined together to create mechanisms to secure and preserve it. However, irrespective of the generation of rich analysis results, this study was undertaken to examine the RDM activities on the global Registry of Research Data Repositories platform (Re3data) to increase its level of visualization. Design/methodology/approach: The study approached the Re3 website, a global registry of research data repositories to collect the data. The researcher specifically assessed the 9 alternative search strategies that are available in the Re3 database; namely subject, content, keyword, metadata standards, quality management, repository languages, software, repository types and country. Findings: It is observed that behaviors related to structured study results are more evident in developed countries as opposed to developing countries, although the U.S. is placed first. Results also indicated that research data is more structured in the case of scientific and statistical formats and disciplinary databases, particularly the life sciences. Overall, the software is mainly used for processing data and the English language is strongly supported. Dublin core metadata is often used to increase the quality of data from analysis. Originality/value: This study presented an overall picture of the research data practices throughout the investigation on the Re3data platform. The research proposed best practices focused on RDM operations to improve the amount of Research Data activities

Solving Trapezoidal Fuzzy Linear Programming Problem using Modified Big-M

<p><i>The fuzzy logic and fuzzy numbers have been applied in many areas of Mathematical Programming. Optimization under uncertainty is one of the most important problem in Mathematical Programming. This paper proposes a Modified Big M method to solve fully fuzzy Trapezoidal linear programming problem with fuzzy decision variables and fuzzy parameters. </i></p&gt