Sistem Repositori Ilmiah Nasional

Transkripsi

1 Sistem Repositori Ilmiah Nasional Hendro Subagyo, PDII-LIPI Lokakarya Nasional Jaringan Perpustakaan, Literatur, dan Informasi Kesehatan Jakarta, 23 Agustus 2016

2 Mengapa perlu Repositori Ilmiah Nasional? Kebutuhan era informasi sumber daya utama = penguasaan, akses dan pemanfaatan informasi basis kekayaan intelektual / pengetahuan modal utama ekonomi kreatif

3 Tuntutan Regulasi RUU Amandemen UU 14/2001 tentang Paten wajib simpan biodiversitas yang dipatenkan RUU Pengganti UU 18/2002 tentang Sistem Nasional P3 Iptek wajib simpan hasil kegiatan penelitian ilmiah wajib simpan data primer kegiatan penelitian ilmiah R-Permenristekdikti xx/2016 tentang Akreditas Jurnal Ilmiah Nasional wajib simpan jurnal ilmih nasional untuk proses akreditasi R-Permenristekdikti xx/2016 tentang Repositori dan Depositori Nasional wajib simpan hasil kegiatan penelitian ilmiah wajib simpan data primer kegiatan penelitian ilmiah Perka LIPI 12/2016 tentang Repositori dan Depositori LIPI wajib simpan hasil kegiatan penelitian ilmiah wajib simpan data primer kegiatan penelitian ilmiah

4 Posisi Litbang Indonesia

5 sustainability generate or gain access sustainability is the ability to generate or gain access to the resources needed to protect and increase the value of the content or service for those who use it JISC - Sustaining Digital Resources: An On-the-Ground View of Projects Today (2009)

6 Network Readiness Index: Indicators World Economic Forum. The Global Information Technology Report 2015

7 Network Readiness Index: Indicators World Economic Forum. The Global Information Technology Report 2015

8 Network Readiness Index 2015 World Economic Forum. The Global Information Technology Report 2015

9 Network Readiness Index 2015 World Economic Forum. The Global Information Technology Report 2015

10 NRI 2015: Indonesia World Economic Forum. The Global Information Technology Report 2015

11 Peneliti: Penyimpanan Data unreliable storage management

12 Peneliti: Volume Data Penelitian

13 Jenis Data Penelitian Data yang sulit didapatkan kembali Observasi (fenomena tertentu pada waktu tertentu atau lokasi dimana data biasanya merupakan data unik dan tak tergantikan) Eksperimental (eksperimen ilmiah dan hasil perhitungan) Kode komputer (termasuk model atau kode sumber simulasi) Data referensi (kanonik atau referensi yang berkaitan misalnya untuk urutan gen,struktur kimia atau teks sastra) Turunan (yang dihasilkan dari pengolahan atau menggabungkan "data mentah" atau data lainnya) Lainnya

14 Perilaku Peneliti: Backup Data Back up data unreliable storage management triwulan tiap tahun pada akhir kegiatan ketika ingat tidak memback up data

15 no preservation = death One of the greatest risks we run in not preserving our own digital assets for ourselves is that we simultaneously cease to preserve our own viability as institutions Halbert & Skinner (2010)

16 Perubahan Pengelolaan dan Layanan Data Publikasi tercetak Katalog Onsite Surat Ontologi (Keyword, Thesaurus) Indeks Klasifikasi, Kategorisasi, Kluster Penelusuran Pustakawan = Literature Expert Publikasi dijital Katalog dijital Online /Socmed Data ilmiah Ontologi (Keyword, Thesaurus) Indeks Klasifikasi, Kategorisasi, Kluster Penelusuran Pustakawan = Data Expert

17 Jumlah output ilmiah, dobel setiap 9 tahun Laporan penelitian Lutz Bornmann, Max Planck Society dan Ruediger Mutz, Swiss Federal Institute of Technology, 2014 Rate per tahun 8-9% tahun % di abad 18 Analisis dari 755 juta referensi tersitir dalam 38 juta publikasi, tahun Scopus 2013: 2,780, : 2,831,406

18 Librarian: new research data management expert For a long time, libraries have always been at the consumption end (of knowledge generation) they do a greate job of gathering and organizing information, and making it available to researchers and students. More and more, libraries have started to get involved in the management of research information Kelechi Okere, Global Sales Director of Pure, Elsevier We have the skill set to organize things. We understand controlled vocabulary. We understand ontologies. We understand organization of information in a way that seems as if it bred into us. The evolution from the print word and subject heading to data made a lot of sense we understand it. So there started to be conversations about what we could do to help people organize, access and store data. MJ Tooey, Health Sciences and Human Services Library at the University of Maryland, Baltimore

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20 Research Data Management Lifecyle Reproducible Research

21 Reproducible Research the data and code used to make a finding are available and they are sufficient for an independent researcher to recreate the finding Peng (2011)

22 Repeat vs Replicate vs Reuse vs Reproduce

23 Why Reproducible Research? For Science Standard to judge scientific claims Science is the systematic enterprise of gathering knowledge... organizing and condensing that knowledge into testable laws and theories American Physical Society

24 Why Reproducible Research? For Science Avoiding effort duplication & encouraging cumulative knowledge development Not only is reproducibility important for evaluating scientific claims, it can also contribute to the cumulative growth of scientific knowledge Kelly, 2006 King, 1995

25 Why Reproducible Research? For Scientist Better work habits Better teamwork Changes are easier Higher research impact Research that is fully reproducible contains more information, i.e. more reasons to use and cite it, than presentation documents merely showing findings

26 Why Reproducible Research? True. But competition means that strangers will read your papers, try to learn from them, cite them, and try to do even better. If you prefer obscurity, why are you publishing? Donoho et.al, 2009

27 Research Pipeline for Reproducible Research (Peng, 2006) Author Processing Code Analytic Code Presentation Code Figures Measured Data Analytic Data Computational Results Tables Papers Numerical Results Text Reader

28 Reproducibility (Peng 2011)

29 Research Reproducibility

30 Kita perlu preservasi dan akses yang memadai untuk data & karya ilmiah riset yang sustainable & reproducible

31 Posisi Layanan LIPI

32 Infrastruktur Skala Besar Berukuran besar Sistem kompleks Melibatkan kepakaran lintas disiplin dengan level tinggi Biaya pemeliharaan dan pemakaian tinggi Pemakai kalangan spesifik: akademisi, industri tertentu Harus ada, tetapi cukup satu di Indonesia Tetapi secara bisnis tidak ekonomis

33 Infrastruktur Informasi Skala Besar LIPI

34 Research Pipeline Repositori Ilmiah Nasional LIPI Author Processing Code Analytic Code Presentation Code Figures Papers & Data Citation Proposa l Adm. Seleksi Measured Data Analytic Data Computatio nal Results Tables Numerical Results Papers Text Reader

35 Sistem Repository Ilmiah Nasional Goal: terciptanya sistem pengelolaan dokumentasi penelitian ilmiah terintegrasi. Sitasi Indeks Harvesting InaSTI Repositori Ilmiah Nasional (RIN) ISJD Search Engine/ Indexing Information Services OJS ISSN Processing Services Data Acquisition Services 35

36 Data Repositori Ilmiah Proposal Data primer (Depositori) Data hasil analisis (table, diagram, chart) Publikasi (artikel) Dataset Karya ilmiah lainnya Prototype + dokumen Informasi paten Images, Videos Metadata Sitasi artikel Sitasi data ID unik (DOI) data & karya ilmiah Link dengan journal (OJS)

37 Federasi Repositori Ilmiah Repositori Child repositori catalog information dataset text file graph data

38 Data Descriptor/Metadata

39 Dataset: mengandung file data, dokumentasi, code, dan metadata Dataverse: arsip (virtual) lengkap, mengandung dataset, dataverse lainnya, tampil di website dan sebagai milik pengguna

40 Prototype Repositori Ilmiah

41 Prototype Repositori Ilmiah

42 Prototype Repositori Ilmiah

43 Prototype Repositori Ilmiah

44 Integrated OJS and Repositori Workflow

45 ... hasil FGD Repositori Ilmiah & Big Data LIPI di Bogor Agustus 2016