Manajemen Data Penelitian Dengan Dataverse: Best Practice Pustakawan Menggunakan Sistem Repositori Ilmiah Nasional LIPI

Nashihuddin, Wahid; Yudhanto, Seno; Surapermana, Ahmad Saefudin; Rishadi, Rishadi

doi:10.21043/libraria.v7i2.6508

Cited by 5 publications

(17 citation statements)

References 5 publications

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“…RIN policy is binding, applies to all RIN users and covers data management, ownership and copyright, depositing/self-archiving, content and metadata, preservation and access and use (Song and Zhu, 2017). The policy is governed by the findable, accessible, interoperable and reusable principles, which emphasize open source (Nashihuddin et al , 2019). To deposit raw research data, a researcher must apply for the creation of a data set or dataverse.…”

Section: Resultsmentioning

confidence: 99%

“…BRIN has the means to store, preserve, quote, analyze and share research data at the RIN, which is open source and uses Dataverse. Researchers, agencies and funders have full control over their research data (Nashihuddin et al , 2019). The data stored consists of quantitative statistical data; and nonstatistical data, which is usually qualitative (textual) in nature; data in digital audio; spatial data; and digital image and video data.…”

Section: Resultsmentioning

confidence: 99%

“…BRIN carries out long-term maintenance and ensures access by converting or migrating formats in accordance with the latest technological developments; moreover, it performs regular back-ups (Nashihuddin et al , 2019). BRIN processes, analyzes and packages all metadata, including the full text of scientific papers, for information dissemination purposes.…”

Section: Resultsmentioning

confidence: 99%

“…BRIN has a data usage policy that permits the reuse of harvested metadata from RIN by storage in another agency’s database. This policy is based on the considerations that the use of metadata in RIN complies with Creative Common Attribution CC BY 4.0.; metadata can be reused and changed in other media as long as the source is included; the use of metadata for commercial purposes requires official permission from the data owner and RIN; and access and reuse of data are controlled and determined by the data owner (Nashihuddin et al , 2019). The data owner produces research data according to research objectives and in a particular context (Faniel et al , 2019).…”

Section: Resultsmentioning

confidence: 99%

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The readiness to implement digital humanities data curation of four institutional repositories in Indonesia

Laksmi,

Suhendra,

Shuhidan

et al. 2023

DLP

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Purpose This study aims to identify the readiness of institutional repositories in Indonesia to implement digital humanities (DH) data curation. Data curation is a method of managing research data that maintains the data’s accuracy and makes it available for reuse. It requires controlled data management. Design/methodology/approach The study uses a qualitative approach. Data collection was carried out through a focus group discussion in September–October 2022, interviews and document analysis. The informants came from four institutions in Indonesia. Findings The findings reveal that the national research repository has implemented data curation, albeit not optimally. Within the case study, one of the university repositories diligently curates its humanities data and has established networks extending to various ASEAN countries. Both the national archive repository and the other university repository have implemented rudimentary data curation practices but have not prioritized them. In conclusion, the readiness of the national research repository and the university repository stand at the high-capacity stage, while the national archive repository and the other university repository are at the established and early stages of data curation, respectively. Research limitations/implications This study examined only four repositories due to time constraints. Nonetheless, the four institutions were able to provide a comprehensive picture of their readiness for DH data curation management. Practical implications This study provides insight into strategies for developing DH data curation activities in institutional repositories. It also highlights the need for professional development for curators so they can devise and implement stronger ownership policies and data privacy to support a data-driven research agenda. Originality/value This study describes the preparations that must be considered by institutional repositories in the development of DH data curation activities.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

The readiness to implement digital humanities data curation of four institutional repositories in Indonesia

Laksmi,

Suhendra,

Shuhidan

et al. 2023

DLP

View full text Add to dashboard Cite

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“…Skema folder pada platform Dataverse Sumber: Dataverse Userguide: https://guides.dataverse.org/en/4.17/user/index.html Pada sistem RIN yang berbasis Dataverse, hirarki penyimpanan terbagi menjadi dua skema, yaitu folder dataverse dan folder dataset. Folder Dataverse adalah wadah kumpulan dari beberapa Dataset dan juga dapat berisi kumpulan Dataverse (sub-dataverse), sedangkan folder Dataset adalah wadah untuk menyimpan dan mengelola data, dokumentasi, kode, dan deskripsi metadata yang menjelaskan Dataset tersebut (Nashihuddin et al, 2020). Melalui sistem ini, skema pengorganisasian metadata deskriptif terdapat pada bagian folder dataset.…”

Section: Skema Dataverse Skema Datasetunclassified

Deskripsi Metadata dalam Manajemen Data Penelitian: Studi Kasus pada Sistem Repositori Ilmiah Nasional

Yudhanto

Mayesti

2021

TIK

Self Cite

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Organizing research data is very important for data and information managers through a research data management mechanism (research data management/MDP) in a repository system. In this mechanism, research data must be organized and described as an effort to provide access. One important aspect of organizing is the availability of metadata. This Study was supported by the Institute of Sciences of Indonesia (LIPI) and the SAINTEK Scholarship from the Ministry of Research and Technology/National Research and Innovation Agency of the Republic of Indonesia (KEMENRISTEK/BRIN) in 2020 and it’s purpose is to identify and describe metadata standards and metadata elements used in research data management in the National Scientific Repository (RIN) system. This study uses a qualitative approach with a case study method. Sources of data come from literature / document studies and direct observation. The results of the study show that the RIN system adopts descriptive metadata from three main standards, they are DublinCore, DataCite, and DDI. As a medium for describing research data in general, the metadata sections provided by the RIN system in the dataset folder are quite large and complete. Of the 35 metadata fields available in the dataset folder in this system, the three metadata standards complement each other with an adaptation of the dominant DDI standard with 32 metadata fields. However, the fields that are available can also be found in other standards, such as the title, subject, or keyword fields that are also found in the DublinCore and DataCite standards. Thus, the metadata fields provided in the RIN system is good enough and sufficient for research data management needs.

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Kompetensi Pustakawan Balitbangtan dalam Pengelolaan Data Penelitian Pertanian

Rushendi,

Kuraesin

2022

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Teknologi informasi semakin pesat saat ini bukanlah merupakan suatu kendala, namun menjadi tantangan dalam meningkatkan layanan perpustakaan, serta menjadi peluang pustakawan untuk mengembangkan kompetensi. Permasalahan yang dihadapi dalam mengelola data hasil penelitian adalah pustakawan hanya berfokus mengelola karya tulis, dan masih jarang menyusun katalogisasi data, metadata, pelestarian, analisis data, dan pengolahan secara tepat. Tujuan pengkajian untuk mengetahui tingkat kompetensi pustakawan/pengelola perpustakaan Balitbangtan dalam pengelolaan data penelitian pertanian. Kajian menggunakan analisis deskriptif metode survei melalui tehnik sampel 44 pustakawan dengan pengumpulan data menyebarkan kuesioner online (e-questionnaire) dengan menggunakan Google Form dan studi literatur yang berkaitan dengan tujuan pengkajian. Pengkajian dilaksanakan Agustus – Desember 2021. Berdasarkan hasil kajian diketahui bahwa pustakawan/pengelola perpustakaan Balitbangtan mampu mengonsep dan memproses kurasi data penelitian pertanian; mampu mendeskripsikan standar meta data berdasarkan analisis deskripsi; mampu mendeskripsikan kata kunci data riset pertanian; dan mampu memberikan pelayanan data penelitian pertanian; serta sebagian pustakawan memohon dukungan kebijakan teknis sistem layanan data penelitian kepada pemangku kebijakan dalam mempersiapkan data/kumpulan data untuk disimpan dan dimasukkan di sistem repositori Balitbangtan.

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Manajemen Data Penelitian Dengan Dataverse: Best Practice Pustakawan Menggunakan Sistem Repositori Ilmiah Nasional LIPI

Cited by 5 publications

References 5 publications

The readiness to implement digital humanities data curation of four institutional repositories in Indonesia

The readiness to implement digital humanities data curation of four institutional repositories in Indonesia

Deskripsi Metadata dalam Manajemen Data Penelitian: Studi Kasus pada Sistem Repositori Ilmiah Nasional

Kompetensi Pustakawan Balitbangtan dalam Pengelolaan Data Penelitian Pertanian

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