Developing Institutional Research Data Repository: A Case Study

2016 ◽  
pp. 51-56 ◽  
Author(s):  
Zhiwu Xie ◽  
Julie Speer ◽  
Yinlin Chen ◽  
Tingting Jiang ◽  
Collin Brittle ◽  
...  
Keyword(s):  
Research Data ◽  
Data Repository ◽  
Institutional Research

scholarly journals Kutatási adatkezelést támogató szolgáltatás a Szegedi Tudományegyetemen

2021 ◽  
Author(s):  
Rozália Zeller ◽  
Szabolcs Hoczopán ◽  
Gyula Nagy
Keyword(s):  
Data Management ◽  
Research Community ◽  
Research Data ◽  
Data Repository ◽  
Institutional Research ◽  
Research Data Management ◽  
International Trends ◽  
Professional Assistance ◽  
Management Recommendations ◽  
The University

Following the national and international trends in mid-2020 the Klebelsberg Kuno Library of the University of Szeged has also started to deal with the issue of research data management. After thorough self-training the library staff studied the Hungarian and international best practices of managing research data. We tried to assess the needs of the institutional research data management habits and the opinion of the researchers of SZTE with a comprehensive questionnaire. We compiled a comprehensive questionnaire to assess the needs of our researchers, learn what they’re thinking about RDM and what kind of practices regarding RDM already exist in the research community. By evaluating the questionnaire we have determined the areas in which the library could provide professional assistance where there was a real need among researchers. Keeping in mind the needs of the research community of University of Szeged we have decided to develop the following services: copyright consulting, RDM trainings for PhD students, theoretical and methodological assistance for RDM, write institutional FAIR data management recommendations. The last four services have been successfully implemented. We also wrote a feasibility study to assess the possibilities of developing our own institutional data repository.

scholarly journals Why is getting credit for your data so hard?

2020 ◽  
Vol 33 ◽  
pp. 01003
Author(s):  
Wouter Haak ◽  
Alberto Zigoni ◽  
Helen Kardinaal-de Mooij ◽  
Elena Zudilova-Seinstra
Keyword(s):  
Data Sharing ◽  
Research Data ◽  
Data Repository ◽  
Institutional Research ◽  
Public Research ◽  
Data Repositories ◽  
Institutional Repositories ◽  
Institutional Data ◽  
Research Organizations ◽  
Existing Data

Institutions, funding bodies, and national research organizations are pushing for more data sharing and FAIR data. Institutions typically implement data policies, frequently supported by an institutional data repository. Funders typically mandate data sharing. So where does this leave the researcher? How can researchers benefit from doing the additional work to share their data? In order to make sure that researchers and institutions get credit for sharing their data, the data needs to be tracked and attributed first. In this paper we investigated where the research data ended up for 11 research institutions, and how this data is currently tracked and attributed. Furthermore, we also analysed the gap between the research data that is currently in institutional repositories, and where their researchers truly share their data. We found that 10 out of 11 institutions have most of their public research data hosted outside of their own institution. Combined, they have 12% of their institutional research data published in the institutional data repositories. According to our data, the typical institution had 5% of their research data (median) published in the institutional repository, but there were 4 universities for which it was 10% or higher. By combining existing data-to-article graphs with existing article-to- researcher and article-to-institution graphs it becomes possible to increase tracking of public research data and therefore the visibility of researchers sharing their data typically by 17x. The tracking algorithm that was used to perform analysis and report on potential improvements has subsequently been implemented as a standard method in the Mendeley Data Monitor product. The improvement is most likely an under-estimate because, while the recall for datasets in institutional repositories is 100%, that is not the case for datasets published outside the institutions, so there are even more datasets still to be discovered.

scholarly journals Building a Dataset Search for Institutions: Project Update

Publications ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 29
Author(s):  
Mannheimer ◽  
Clark ◽  
Espeland ◽  
Hagerman
Keyword(s):  
The United States ◽  
Research Data ◽  
Data Repository ◽  
Institutional Repository ◽  
Institutional Research ◽  
Data Repositories ◽  
Search Tool ◽  
Metadata Harvesting ◽  
Data Libraries ◽  
Repository Software

Most out-of-the-box institutional repository systems do not provide the workflows and metadata features required for research data. Consequently, many libraries now support two institutional repository systems—one for publications, and one for research data—even when there are nearly a thousand data repositories in the United States, many of which provide services and policies that ensure their trustworthiness and suitability for research data. Libraries are either increasing spending by purchasing data repository solutions from vendors, or replicating work by building, customizing, and managing individual instances of data repository software. This article gives an update on a potential solution to this issue: An in-progress prototype for an open source Dataset Search tool that promotes discovery and reuse of institutional research datasets through automatic metadata harvesting and search engine optimization. Once finished, the Dataset Search tool has the potential to support three key impacts: Increasing discovery, reuse, and citation of research data; reinforcing the idea that research data are a legitimate scholarly product; and promoting community-owned systems that require less resource expenditure.

scholarly journals BUILDING A GEOGRAPHIC DATA REPOSITORY FOR URBAN RESEARCH WITH FREE SOFTWARE – LEARNING FROM Observatorio.CEDEUS.cl

2017 ◽  
Vol XLII-4/W2 ◽  
pp. 147-153
Author(s):  
S. Steiniger ◽  
H. de la Fuente ◽  
C. Fuentes ◽  
J. Barton ◽  
J.-C. Muñoz
Keyword(s):  
Spatial Data ◽  
Data Exchange ◽  
Data Communication ◽  
Research Data ◽  
Sustainable Urban Development ◽  
Research Centre ◽  
Data Repository ◽  
Data Repositories ◽  
Geographic Data

The recent trend towards open data and open science as well as a demand for holistic and interdisciplinary research requires platforms that allow the distribution and exchange of research data, including geographic information. While the requirements and benefits of data exchange are widely discussed, there are few proposals on how to implement data platforms that not only permit the exchange of research data among researchers, but also permit to distribute research results and data to the interest public. We elaborate what points are important for implementing a (geographic) data repository and propose then to adopt the concept of Spatial Data Infrastructures (SDI) as a solution for the implementation of research data repositories. We present as a case study the geographic data and document repository of the Chilean research Centre on Sustainable Urban Development (CEDEUS), the CEDEUS Observatory. Besides the infrastructure to host and distribute data, communication tools are an important component of such a data repository service. For this case study we analyse which things have worked well and which things have not worked well based on the experiences collected during three years of operation. We close with some recommendations for the implementation of data repositories for research.

scholarly journals The on-premise data sharing infrastructure e!DAL: Foster FAIR data for faster data acquisition

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Daniel Arend ◽  
Patrick König ◽  
Astrid Junker ◽  
Uwe Scholz ◽  
Matthias Lange
Keyword(s):  
Data Management ◽  
Data Storage ◽  
Best Practice ◽  
Research Process ◽  
Research Data ◽  
Primary Data ◽  
Data Repository ◽  
Plant Genomics ◽  
Quality Of Data

Abstract Background The FAIR data principle as a commitment to support long-term research data management is widely accepted in the scientific community. Although the ELIXIR Core Data Resources and other established infrastructures provide comprehensive and long-term stable services and platforms for FAIR data management, a large quantity of research data is still hidden or at risk of getting lost. Currently, high-throughput plant genomics and phenomics technologies are producing research data in abundance, the storage of which is not covered by established core databases. This concerns the data volume, e.g., time series of images or high-resolution hyper-spectral data; the quality of data formatting and annotation, e.g., with regard to structure and annotation specifications of core databases; uncovered data domains; or organizational constraints prohibiting primary data storage outside institional boundaries. Results To share these potentially dark data in a FAIR way and master these challenges the ELIXIR Germany/de.NBI service Plant Genomic and Phenomics Research Data Repository (PGP) implements a “bring the infrastructure to the data” approach, which allows research data to be kept in place and wrapped in a FAIR-aware software infrastructure. This article presents new features of the e!DAL infrastructure software and the PGP repository as a best practice on how to easily set up FAIR-compliant and intuitive research data services. Furthermore, the integration of the ELIXIR Authentication and Authorization Infrastructure (AAI) and data discovery services are introduced as means to lower technical barriers and to increase the visibility of research data. Conclusion The e!DAL software matured to a powerful and FAIR-compliant infrastructure, while keeping the focus on flexible setup and integration into existing infrastructures and into the daily research process.

Perbandingan harga saham, volume transaksi dan return saham sebelum dan sesudah terjadi pandemi covid-19 pada PT Agung Podomoro Land, Tbk

2021 ◽  
Vol 5 (4) ◽  
pp. 720
Author(s):  
Anggun Putri Romadhina ◽  
Eka Kusuma Dewi
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Stock Price ◽  
Research Data ◽  
Paired Sample ◽  
First Case ◽  
Significant Difference ◽  
Before And After ◽  
Stock Transaction

The first Covid-19 case in Indonesia was announced on March 2, 2020. This study aims to determine whether there is a significant difference in stock prices, stock transaction volume and stock returns due to the COVID-19 pandemic (case study at PT. Agung Podomoro Land, Tbk). This research data was taken 90 days before and 90 days after the announcement of the first case of COVID-19 in Indonesia. The data was processed by paired sample t-test, using SPSS version 20. From the results of data processing, it was shown that there was a significant difference in stock prices before and after the announcement of the first case of covid-19 in Indonesia. This is indicated by a significance value of 0.000 < 0.05 where the stock price has decreased compared to before the Covid-19 case. Meanwhile, the volume of stock transactions also showed a significant difference with a significance value of 0.007 <0.05, where the volume of stock transactions after the announcement showed a decrease. Likewise, stock returns show a significant difference with a significance value of 0.025 < 0.05 where stock returns have decreased after the announcement of the first case of covid-10 in Indonesia.  

KEPEMIMPINAN LURAH DALAM PENGELOLAAN BANK SAMPAH DI KELURAHAN RAYA KECAMATAN SINGKEP BARAT KABUPATEN LINGGA PROVINSI KEPULAUAN RIAU

2021 ◽  
pp. 13-27
Author(s):  
Agung Nurrahman ◽  
Gatiningsih Gatiningsih ◽  
Muhammad Tri Syaputra
Keyword(s):  
Environmental Issues ◽  
Research Data ◽  
Community Leaders ◽  
Structured Interviews ◽  
Political Will ◽  
Descriptive Research ◽  
Qualitative Descriptive ◽  
Waste Bank

This research focuses on how leadership has a major role in addressing environmental issues, especially through the garbage bank program as a form of case study. Furthermore, the problems that occur in the midst of society are often rely solely on political will or political desire to solve them. The research is to know and learn Lurah's (head of village) leadership in the management of waste banks specifically. This research is qualitative descriptive research. Data collection techniques through structured interviews, documentation and observations. Researchers conducted an analysis using leadership theory from Yukl, where the theory discusses leadership comprehensively. Researchers only focus on five parts of the concept that are considered relevant, namely: visionary, guidance, affiliative, democratic and communicative concepts. The results of this study based on these dimensions are good enough Lurah (head of village) leadership. But there are several things that are considered able to optimize the running of the program through the role of Lurah (Head of village) leadership, namely: first, involving active knots and community leaders such as MUI, academics to support scientific aspects, and professionals in the field of practical management. Keywords: Leadership, Head of Village, Environmental Issues, Waste Management, Waste Bank  

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