Evaluasi Implementasi Kebijakan Sistem Repositori Ilmiah Nasional (Rin)

2021 ◽  
Vol 5 (2) ◽  
pp. 80
Author(s):  
Vivi Elvina Panjaitan
Keyword(s):  
Qualitative Research ◽  
Research Data ◽  
Data Management System ◽  
Primary Data ◽  
Target Groups ◽  
Research Data Management ◽  
Share Data ◽  
Technical Guidance

ABSTRACTNumbers of management, storage, and preservation of research data problems had been the rationales why national scientific repository (RIN) system was implemented. To measure its success, the present study evaluated, analyzed problems, and provided recommendations using descriptive exploratory qualitative research methods with interviews as the primary data. In terms of the effectiveness, the results showed that the RIN system objectives provided a nationally integrated interoperability research data management system, ensuring long-term archiving and access had been achieved whereas the awareness of researchers to share data and sustainability plans had not been achieved. Based on its efficiency, PDDI LIPI had pursued many activities and strategies. In accordance with its adequacy, the existence of RIN system was able to answer the existing research data problems while the problem of continuity of input of research data and the sustainability of research had not been achieved. In regard to its equalization, RIN system was intended to all professions that carried out research, in which the socialization activities and technical guidance to researchers in relevant institutions were conducted. In coping with its responsiveness, all target groups still could not experience it because the follow-up activity of the target groups after knowing RIN system was still minimum. Hence, it was advised that the target group from both internal LIPI, external LIPI, and PDDI LIPI acted as the implementors. The present study concluded that the implementation of RIN system had not been optimally implemented and still needed improvements. ABSTRAKPermasalahan pengelolaan, penyimpanan, pelestarian data penelitian mendorong dilakukannya implementasi kebijakan sistem RIN. Untuk mengukur keberhasilannya, penulis mengevaluasi, menganalisis permasalahan dan memberikan rekomendasi dengan menggunakan metode penelitan kualitatif deskriptif melalui data primer yaitu wawancara dan data sekunder. Dari efektivitasnya diperoleh hasil bahwa tujuan sistem RIN menyediakan sistem interoperabilitas pengelolaan data penelitian terintegrasi secara nasional, menjamin pengarsipan dan pengaksesan jangka panjang telah tercapai sedangkan kesadaran peneliti untuk berbagi data dan rencana keberlanjutan belum tercapai. Berdasarkan efisiensinya, PDDI LIPI telah mengupayakan banyak kegiatan dan strategi. Berdasarkan kecukupannya, keberadaan sistem RIN mampu menjawab permasalahan data penelitian yang dihadapi sedangkan permasalahan kontinuitas penginputan data penelitian, keberlanjutan penelitian belum tercapai. Berdasarkan pemerataannya, sistem RIN ditujukan kepada seluruh profesi yang melaksanakan penelitian, bukan sekelompok golongan namun kegiatan sosialisasi dan bimbingan teknis lebih banyak kepada peneliti di instansi yang memiliki badan penelitian pengembangan serta perguruan tinggi. Berdasarkan responsivitasnya, belum dapat dirasakan oleh seluruh target sasaran dikarenakan tindaklanjut dari para target sasaran setelah mengenal sistem RIN masih rendah. Maka perlu rekomendasi kepada target sasaran baik dari internal LIPI, eksternal LIPI maupun PDDI LIPI sebagai implementor. Oleh karena itu dapat disimpulkan bahwa implementasi kebijakan sistem RIN belum berjalan dengan optimal dan masih perlu ditingkatkan.

scholarly journals Perception of Researchers & Academicians of Parul University towards Research Data Management System & Role of Library

2020 ◽  
Vol 40 (03) ◽  
pp. 139-146 ◽  
Author(s):  
Anjana R Bunkar ◽  
Dhaval D. Bhatt
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
Developed Countries ◽  
Research Data ◽  
Data Management System ◽  
The Public ◽  
Research Data Management ◽  
Initial Stage

Research data management is a system that helps in archiving and retrieving of research data to reuse and preserving them for long term use. Many universities in developed countries have already started providing RDM services to their researchers and academicians. In India, it is still in the initial stage. The purpose of the present study is to investigate the perceptions of researchers and academicians of Parul University on research data management and research data sharing. It also explores the ways the researchers preserved their research data for future use. It also explores the ways the library can take initiatives to encourage and extend support to the researchers and academicians to the organisation, preservation, and sharing of research data. To investigate and study the problem 100 questionnaires were distributed. There are 88 responses we received out of 100. The study revealed that the majority of respondents were agreeing about the research data sharing and free accessibility of research data to browse and reuse. Researchers are very much interested and agreed in the library’s involvement in organizing and preservation of research data. Researchers and faculty members are more concerned about their intellectual property rights while sharing the data on the public domain.

scholarly journals Scientific Research Data Management for Soil-Vegetation-Atmosphere Data – The TR32DB

2012 ◽  
Vol 7 (2) ◽  
pp. 68-80 ◽  
Author(s):  
Constanze Curdt ◽  
Dirk Hoffmeister ◽  
Guido Waldhoff ◽  
Christian Jekel ◽  
Georg Bareth
Keyword(s):  
Data Management ◽  
Interdisciplinary Research ◽  
Management System ◽  
Scientific Research ◽  
Research Data ◽  
Data Management System ◽  
Research Data Management ◽  
Interdisciplinary Research Project ◽  
Practical Experiences

The implementation of a scientific research data management system is an important task within long-term, interdisciplinary research projects. Besides sustainable storage of data, including accurate descriptions with metadata, easy and secure exchange and provision of data is necessary, as well as backup and visualisation. The design of such a system poses challenges and problems that need to be solved.This paper describes the practical experiences gained by the implementation of a scientific research data management system, established in a large, interdisciplinary research project with focus on Soil-Vegetation-Atmosphere Data.

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.

scholarly journals BEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data

2021 ◽  
Vol 9 ◽  
Author(s):  
Javad Chamanara ◽  
Jitendra Gaikwad ◽  
Roman Gerlach ◽  
Alsayed Algergawy ◽  
Andreas Ostrowski ◽  
...  
Keyword(s):  
Data Management ◽  
Management System ◽  
Research Data ◽  
Environmental Data ◽  
The Self ◽  
Data Management System ◽  
Maturity Model ◽  
Ecological Data ◽  
Self Assessment ◽  
Research Data Management

Obtaining fit-to-use data associated with diverse aspects of biodiversity, ecology and environment is challenging since often it is fragmented, sub-optimally managed and available in heterogeneous formats. Recently, with the universal acceptance of the FAIR data principles, the requirements and standards of data publications have changed substantially. Researchers are encouraged to manage the data as per the FAIR data principles and ensure that the raw data, metadata, processed data, software, codes and associated material are securely stored and the data be made available with the completion of the research. We have developed BEXIS2 as an open-source community-driven web-based research data management system to support research data management needs of mid to large-scale research projects with multiple sub-projects and up to several hundred researchers. BEXIS2 is a modular and extensible system providing a range of functions to realise the complete data lifecycle from data structure design to data collection, data discovery, dissemination, integration, quality assurance and research planning. It is an extensible and customisable system that allows for the development of new functions and customisation of its various components from database schemas to the user interface layout, elements and look and feel. During the development of BEXIS2, we aimed to incorporate key aspects of what is encoded in FAIR data principles. To investigate the extent to which BEXIS2 conforms to these principles, we conducted the self-assessment using the FAIR indicators, definitions and criteria provided in the FAIR Data Maturity Model. Even though the FAIR data maturity model is developed initially to judge the conformance of datasets, the self-assessment results indicated that BEXIS2 remarkably conforms and supports FAIR indicators. BEXIS2 strongly conforms to the indicators Findability and Accessibility. The indicator Interoperability is moderately supported as of now; however, for many of the lesssupported facets, we have concrete plans for improvement. Reusability (as defined by the FAIR data principles) is partially achieved. This paper also illustrates community deployment examples of the BEXIS2 instances as success stories to exemplify its capacity to meet the biodiversity and ecological data management needs of differently sized projects and serve as an organisational research data management system.

scholarly journals How long can we build it? Ensuring usability of a scientific code base

2021 ◽  
Vol 16 (1) ◽  
pp. 11
Author(s):  
Klaus Rechert ◽  
Jurek Oberhauser ◽  
Rafael Gieschke
Keyword(s):  
Data Management ◽  
Source Code ◽  
Research Data ◽  
Scientific Contribution ◽  
Scientific Publications ◽  
Research Data Management ◽  
Code Base

Software and in particular source code became an important component of scientific publications and henceforth is now subject of research data management.  Maintaining source code such that it remains a usable and a valuable scientific contribution is and remains a huge task. Not all code contributions can be actively maintained forever. Eventually, there will be a significant backlog of legacy source-code. In this article we analyse the requirements for applying the concept of long-term reusability to source code. We use simple case study to identify gaps and provide a technical infrastructure based on emulator to support automated builds of historic software in form of source code.  

scholarly journals Research data management and services: Resources for novice data librarians

2017 ◽  
Vol 78 (5) ◽  
pp. 274 ◽  
Author(s):  
Sarah Barbrow ◽  
Denise Brush ◽  
Julie Goldman
Keyword(s):  
Life Cycle ◽  
Data Management ◽  
Academic Libraries ◽  
Research Data ◽  
Research Data Management ◽  
Academic Fields ◽  
Data Life Cycle ◽  
Management Plans ◽  
Share Data

Research in many academic fields today generates large amounts of data. These data not only must be processed and analyzed by the researchers, but also managed throughout the data life cycle. Recently, some academic libraries have begun to offer research data management (RDM) services to their communities. Often, this service starts with helping faculty write data management plans, now required by many federal granting agencies. Libraries with more developed services may work with researchers as they decide how to archive and share data once the grant work is complete.

scholarly journals CaosDB—Research Data Management for Complex, Changing, and Automated Research Workflows

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 83 ◽  
Author(s):  
Timm Fitschen ◽  
Alexander Schlemmer ◽  
Daniel Hornung ◽  
Henrik tom Wörden ◽  
Ulrich Parlitz ◽  
...  
Keyword(s):  
Data Management ◽  
Data Model ◽  
Query Language ◽  
Research Data ◽  
Data Management System ◽  
Biomedical Sciences ◽  
Seamless Integration ◽  
Research Data Management ◽  
The Status ◽  
Data Acquisition And Processing

We present CaosDB, a Research Data Management System (RDMS) designed to ensure seamless integration of inhomogeneous data sources and repositories of legacy data in a FAIR way. Its primary purpose is the management of data from biomedical sciences, both from simulations and experiments during the complete research data lifecycle. An RDMS for this domain faces particular challenges: research data arise in huge amounts, from a wide variety of sources, and traverse a highly branched path of further processing. To be accepted by its users, an RDMS must be built around workflows of the scientists and practices and thus support changes in workflow and data structure. Nevertheless, it should encourage and support the development and observation of standards and furthermore facilitate the automation of data acquisition and processing with specialized software. The storage data model of an RDMS must reflect these complexities with appropriate semantics and ontologies while offering simple methods for finding, retrieving, and understanding relevant data. We show how CaosDB responds to these challenges and give an overview of its data model, the CaosDB Server and its easy-to-learn CaosDB Query Language. We briefly discuss the status of the implementation, how we currently use CaosDB, and how we plan to use and extend it.

scholarly journals Model Example Non Example Dalam Pembelajaran Tajwid

2020 ◽  
Vol 5 (1) ◽  
pp. 23
Author(s):  
Partono Partono ◽  
Hamengkubuwono Hamengkubuwono ◽  
Jeny Fransiska
Keyword(s):  
Qualitative Research ◽  
Critical Thinking ◽  
Student Learning ◽  
Learning Outcomes ◽  
Student Learning Outcomes ◽  
Learning Model ◽  
Research Data ◽  
Image Display ◽  
Data Sources ◽  
Primary Data

The problem that often occurs to teachers when teaching is that many students are less eager to learn. Therefore, it is necessary to have a new innovation from a teacher to overcome this, namely by using the example non-example model, which is a learning model that uses an image display to be analyzed, where the learning model is aimed at student activeness that allows the teacher to stimulate student enthusiasm by making their vital organs move and focus on tajwid learning in the TPQ Hikmatun Najah Blora so that students can be more active because they themselves will play a role in analyzing the image of verse fragments. This study is included in the category of descriptive qualitative research with the data obtained sourced from primary data sources, namely research main data obtained directly from research data sources namely respondents by interview, observation and documentation. The results of this study indicate that the use of the example non-example model in Tajweed learning at TPQ Hikmatun Najah Blora adds more effectiveness because it can affect student learning outcomes because students become active because it raises the student's thinking and critical thinking so that it raises a high curiosity towards the material delivered.

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