Career Trajectories of Japanese Researchers and Institutional Attributes (1980–2020)

The dataset bundles two complementary comma-separated values (CSV) files describing the career progression of researchers from doctoral graduation to assistant professor (AP) and full professor (FP) appointments, together with a lookup table that standardizes institutional attributes. All records were aggregated from researchmap profiles and curated to support analyses of academic mobility and institutional characteristics focused on the 1980–2020 period. The two files can be used independently or joined through shared institution name fields. Research Asset Characteristic: Longitudinal depth: 40 years of academic career data. Institutional linkage: Standardized mapping of 9,500+ institutions. Cross-disciplinary comparability: Enables analysis across all academic domains. Policy relevance: Supports evaluation of Japanese higher education and mobility policies. File Inventory data/dr-ap-fp.csv – 78,208 rows × 16 columns capturing individual researcher timelines between doctoral, AP, and FP stages during 1980–2020. data/机构属性映射表.csv – 9,500 rows × 6 columns mapping original institution labels to standardized names and attributes. Field Reference data/dr-ap-fp.csv Field Type / Format Description researcher_user_id string Unique identifier of each researcher in the original source. gender string (`M`, `F`, or blank) Reported gender; empty if unknown. discipline string (`Discipline 1 | Discipline 2`) Hierarchical discipline designation(s) separated by a vertical bar. disciplineCount integer Count of distinct discipline entries listed in `discipline`. research string Detailed research focus tags; may contain multiple labels. doctorDegreeDate year (YYYY) year (YYYY) | Doctoral graduation year; blank if missing. AP_from_date / AP_to_date year (YYYY) Start and end years of the assistant professor appointment; `9999` indicates ongoing roles. FP_from_date / FP_to_date year (YYYY) Start and end years of the full professor appointment; `9999` indicates ongoing roles. doctor_to_ap numeric Years between doctoral graduation and first AP appointment. ap_to_fp numeric Years between AP and FP appointments. doctor_to_fp numeric Total years from doctoral graduation to FP appointment. DR_affiliation string Institution at the doctoral stage. AP_affiliation string Institution at the assistant professor stage. FP_affiliation string Institution at the full professor stage. cohort string Custom cohort label (e.g., `cohort84`). data/机构属性映射表.csv(institute mapping.csv) Field Type / Format Description original_institute string Institution name as captured in the dr-ap-fp data target to affiliation college string Standardized institution name. college_country string Country name in Chinese. zone string Geographical grouping (e.g., `日本`, `日本海外`). operation_type string Governance type such as `公立`, `私立`, or `国立`. college_type string Institution category (e.g., `学府`, `研究所`); blank if not assigned. Data Quality and Processing Tips UTF-8 encoding includes Japanese and Chinese characters; ensure import tools preserve multi-language text. Year fields store four-digit years only; supplement with external data if full dates are required. Interval fields (`doctor_to_ap`, `ap_to_fp`, `doctor_to_fp`) may contain blanks; handle missing values prior to modelling. Harmonise `cohort` labels if they are used analytically (e.g., remove explanatory suffixes). Suggested Use Cases Estimate average promotion intervals between doctoral, AP, and FP stages across 1980–2020 and compare by discipline or gender. Join institutional attributes to external rankings or geographic datasets using the mapping table. Visualise researcher mobility flows between Japanese and overseas institutions during the observed period. Contact and Additional Notes Document any revisions or new fields in the Zenodo description changelog. Clarify the access request workflow in the restricted access instructions (e.g., email address and required information). For access requests or additional details, [e-mail] and include both your institutional affiliation and intended use of the dataset.