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"Industrial mineral resources are scattered abundantly throughout Indonesia. However they have not been afforded serious development. As a result, domestic production cannot fulfill the demand for raw materials required by downstream industries. An approach to solve this problem is by providing capital and technical assistance for industries involved in industrial mineral mining. IN this case the R&D are required to provide technical assistance and recommendations to such industries in terms of obtaining capital from the government. Such a management is expected to enhance the development of industrial minerals as well as improve their added value."

"ABSTRAKManajemen data penelitian perlu dilakukan oleh setiap lembaga penelitia nuntuk menjamin integritas dan keberadaan data penelitian serta mengorganisasikan data sepanjang siklus penelitian hingga penggunaan kembali. Penelitian ini bertujuan untuk menyusun rancangan prosedur manajemen data penelitian di Badan Litbang SDM Kementerian Kominfo sebagai pedoman melaksanakan aktivitas manajemen data penelitian. Berdasarkan hasil perbandingan framework manajemen data yang dilakukan, konsep data life cycle yang digunakan penelitian ini terdiri dari 7 fase yaitu planning and discovery atau perencanaan dan penemuan data, collecting atau pengumpulan data, processing atau pemrosesan data, analyzing atau analisis data, preserving atau preservasi data, publishing and sharing atau publikasi dan berbagi data, dan fase terakhir data reuse atau penggunaan ulang data, dengan aktivitas crosscutting yang dilakukan sepanjang fase. Penelitian ini dilakukan dengan pendekatan kualitatif dengan pengumpulan data melalui wawancara, sedangkan analisis data dilakukan dengan metode thematic analysis. Rancangan prosedur manajemen data penelitian ini disusun berdasarkan proses atau aktivitas yang sudah dilakukan maupun aktivitas yang idealnya dilaksanakan dalam prosedur manajemen data penelitian. Validasi analisis data dilakukan secara berjenjang dalam 3 iterasi. Hasil dari penelitian ini adalah rancangan standar operasional prosedur SOP manajemen data penelitian yang sesuai dengan kondisi organisasi Badan Litbang SDM. Rancangan prosedur yang disusun diharapkan dapat memberikan pedoman bagi peneliti Badan Litbang SDM Kominfo untuk melakukan aktivitas manajemen data penelitian.

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Research data management need to be done by each research institution to ensure the integrity and availability of data research and organizes the data throughout the research cycle. This study aims to design research data management procedures in ICT Research and HR Development Agency Ministry of Communication and Information Technology MCIT as guidelines for carrying out activities of research data management. Based on the comparison results of framework data management, the concept of data life cycle used in this study consists of seven phases planning and discovery of data, collecting the data, processing the data, analyzing the data, preserving the data, publishing and sharing of data and last phase was data reuse, with a crosscutting activity conducted throughout the phase. This research was conducted with a qualitative approach to collecting data through interviews, while data analysis was conducted using thematic analysis. The design of this research data management procedures prepared by the process or activity that has been performed as well as activities that would ideally be undertaken in research data management procedures. Validation of data analysis is performed gradually in three iterations. Result from this study is a design of standard operating procedures SOP for research data management which is appropriate for ICT Research and HR Development Agency organizational conditions. The design of procedures was expected to provide guidance for researchers in ICT Research and HR Development Agency ndash MCIT to conduct research data management activities."

"Filling a real knowledge gap, this handbook and ready reference is both modern and forward-looking in its emphasis on the "bench to bedside" translational approach to drug development. Clearly structured into three major parts, the book stakes out the boundaries of peptide drug development in the preclinical as well as clinical stages. The first part provides a general background and focuses on the characteristic strengths and weaknesses of peptide drugs. The second section contains five cases studies of peptides from diverse therapeutic fields, and the lessons to be learned from them, while the final part looks at new targets and opportunities, discussing several drug targets and diseases for which peptide drugs are currently being developed."

"[This work, in co-operation with ABB Research, Deutsche Telekom AG Laboratories, EMC2 Advanced Technology Solutions, IBM Research, Intel Research, Microsoft Research.Philips Research, and SAP Research, develops a systematic approach to performance measurement for industrial research organizations in innovation-driven companies.The following questions are addressed :(1) Which research goals do research departments have?(2) Which KPIs do they use to monitor the achievement of these goals?(3) Is there a systematic best-practice approach to selecting KPIs for performance goals?The outcome is a complete set of eleven performance clusters, such as the transfer of research results to the development or other organizational departments, and each cluster has its own set of KPIs. The eleven clusters are : technology transfer, future business opportunities, technical achievements, intellectual property, operational excellence, talent pool, image, publications, presence in scientific community, collaboration with academia, collaboration with partners and customers., This work, in co-operation with ABB Research, Deutsche Telekom AG Laboratories, EMC2 Advanced Technology Solutions, IBM Research, Intel Research, Microsoft Research.Philips Research, and SAP Research, develops a systematic approach to performance measurement for industrial research organizations in innovation-driven companies.The following questions are addressed :(1) Which research goals do research departments have?(2) Which KPIs do they use to monitor the achievement of these goals?(3) Is there a systematic best-practice approach to selecting KPIs for performance goals?The outcome is a complete set of eleven performance clusters, such as the transfer of research results to the development or other organizational departments, and each cluster has its own set of KPIs. The eleven clusters are : technology transfer, future business opportunities, technical achievements, intellectual property, operational excellence, talent pool, image, publications, presence in scientific community, collaboration with academia, collaboration with partners and customers.]"