Search

Since its launch in 1996, the Social Science Japan Data Archive (SSJDA) has been collecting and storing raw data provided by depositors that are obtained mainly from social surveys. These data are then widely shared for academic purposes, or secondary analysis in particular. Although SSJDA has long been responsible for creating the metadata, a new self-archiving system was developed recently that allows the depositors to register their raw data and create the metadata by themselves. This self-archiving system is expected to improve the efficiency of data archiving and sharing in the long run; however, there are also several challenges to overcome. For example, many depositors, including academic researchers, are unexperienced in creating the metadata in a FAIR manner. Therefore, SSJDA is also planning to provide training programs, such as self-learning materials to the depositors.

This poster presentation illustrates how the Social Science Japan Data Archive (SSJDA) has managed data-sharing good governance that is both ethical and effective. By ethical, we mean that data are shared with users under the terms and conditions provided by the SSJDA, and thus, individual respondents' anonymity is protected. By effective, we mean that the secondary use of data renders research outputs, which provide credits to and become incentives for depositors, hence forming a positive feedback loop among the SSJDA, depositors, and users. The SSJDA has developed and implemented various principles, practices, and tools to attain such good governance in data sharing. First, the related principles cover the whole data-sharing process. For example, different eligibility criteria for access are being set based on the academic status of the users. There are also sharing periods for most of the data, and the users are allowed to choose if they need an extension or to delete the data and terminate data sharing. Second, these principles are put into practice by professional staff who have data-sharing expertise. For example, the SSJDA's staff keep monitoring whether there are misrepresentations in applications submitted by users or if there are any users who have not deleted the data after the sharing period has expired. These staff also respond to user-provided inquiries on virtually any aspects of secondary use. Finally, the SSJDA has developed a its own system called "SSJDA Direct," which serves as a tool that can be used to put principles into practice. SSJDA Direct is a one-stop online service that allows users to search for deposited data and its metadata, apply for secondary use, download the data, and report their research outputs. The SSJDA is continuing to reinforce this system to further improve its data-sharing governance.

Additional file 15. Histological images for donor3_hSSCs and donor5_hSSCs cultured with BMP2 or TGFβ1 for 28 days. Scale bars = 500 μm.

Additional file 20. Micro-CT and histological images in the samples transplanted with hSSCs. IHC images for COL2 with red frame have the area positively stained, and images with blue frame were except for quantification because of non-specific staining. IHC images for SOX9 with yellow frame represents the presence of SOX9 positive cells.

Additional file 4. Chondrogenic pellet culture of mASCs and mSSCs in chondrogenic basal media at day 14. Representative data of macroscopic images and histology are shown.

Additional file 9. The alteration of gene expression of TGFβ superfamily receptors (A), ligands, and chondrogenic markers (B) during chondrogenic culture of mSSCs and mASCs. Data are expressed as Mean ± SD for each lot, and each shape of points represent individual lots.

Additional file 6. Histological features for fibrous cartilage or ectopic cartilage development after transplantation with mouse ASCs.

Additional file 8. Saf-O and IHC for pSmad1 and pSmad2 of in vivo specimens of transplanted with mSSCs or mASCs. Representative data are shown. Scale bars = 100 μm.

Additional file 5. Gene expression of chondrogenic marker in the mASCs and mSSCs cultured with BMP2, TGFβ1, or their combination at day 14. Data are collected from over three independent lots and presented as a box plot with dot plot.

Additional file 7. Extended data in mouse SSCs transplantation group without in vivo chondrogenesis. (A) In samples which defect site is close to enthesis, host synovial tissue infiltrated to defect site and inhibited in vivo chondrogenesis, but transplanted mSSCs existed within granulation tissue with unspecified state. (B) Synovial infusions must be observed in samples with patellar dislocation. Notably, IHC for GFP implies vessel like structure built by transplanted mSSCs. (C) In the samples with in vivo chondrogenesis, transplanted mSSCs existed with unspecified state in bone marrow region underneath neo cartilage.

The Social Science Japan Data Archive (SSJDA) is an institution that collects and stores raw data from statistical and social surveys for safekeeping, and provides access for its secondary use in academic endeavors. It is a core part of the Center for Social Research and Data Archives (CSRDA) in the Institute of Social Science at The University of Tokyo. To support empirical research in the social sciences in Japan, data collection and storage in SSJDA have been smoothly conducted since 1996. Nearly 200 institutions, organizations, and individual researchers have deposited data with SSJDA, and over 2000 data sets have been made available in the public domain thus far. CSRDA was designated as a “Joint Usage/Research Center” by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) beginning in 2010, and was selected for the Promotion of Science Humanities and Social Sciences Data Infrastructure Construction Program by the Japan Society for the Promotion of Science (JSPS) in 2018. Through this program, we have improved SSJDA Direct (Data Download System) and added an online function for a deposit procedure which allows depositors to check the status of their data cleaning and usage from their personal page. It is possible to increase the level of convenience enjoyed by depositors, as well as to increase the quantity of data that is deposited and shared with SSJDA. The improvement of SSJDA Direct contributes to research in the humanities and social sciences in Japan, and will lead to the development of data archives in the future.

Social Science Japan Data Archive (SSJDA) has developed DDI implementation projects. We present two ongoing projects and a future task in SSJDA. The first implementation project is the Nesstar system operation since 2012. Some datasets which are provided from SSJDA are available in the Nesstar system and the number of access and users are increasing. Since mutual link with SSJDA's website is also started, cooperation between services is working more effectively. The second project is development of the software Easy DDI Organizer (EDO). EDO is an open source tool for editing and managing a metadata along with data lifecycle. Our future task is to provide users with tools to encourage users to understand and use social research. Panel surveys usually have complex structures that impede analysis. At the same time, I would like to integrate these multiple projects and improve the process of data archiving work. Discussion of these projects and future issues.

The purpose of this article is to explore the relationship between dropout from higher education and social class origin. It focuses on the following three points; 1) to investigate the pattern of association between class origin and the risk of dropout; 2) to compare the impact of class origin on dropout among several educational transition stages; 3) to examine the trends in the effect of class origin on dropout from higher education. In order to conduct the empirical analysis, large-scale datasets which were merged from various Japanese national representative survey datasets, such as the Social Stratification and Mobility surveys (SSM), Japanese General Social Surveys (JGSS), and Japanese Life-course Panel Surveys (JLPS) are used. The risk of dropout is estimated using binary logit models, rare-event logit models, and transition models. Results show that the risk of dropout from higher education is affected by class origin. Non-manual and agricultural classes are less likely to drop out, while manual and self-employed classes are more likely to drop out from higher education. As for dropout from secondary education, the same pattern of inequality of the risk of dropout among classes is observed. The degree of impact of class origin on dropout is smaller than that on entering into next stage of education. There are no trends in the effects of class origin on dropout. This finding supports Maximum Maintained Inequality (MMI) hypothesis because educational expansion did not affect the pattern of educational inequality including dropping out stage. In conclusion, stable, huge inequality of dropout among social classes is found. Class origin is crucial factor for predicting the risk of dropout from higher education, also a long time ago even now., 本研究は，科学研究費・特別推進研究（25000001）および基盤研究C（16K04029），2016年度参加者公募型共同研究（二次分析研究会テーマB）の成果の一部である。