인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Macrostrat is a platform for deep‐time geoscientific research that integrates stratigraphic columns and geologic maps into a digital description of the crust. The database and supporting software track crustal evolution and provide location‐based geological information to geoscience end users. Macrostrat houses multiple scales of mapping and stratigraphic data, from continent‐ and basin level summaries to single quadrangles and measured sections. Currently, Macrostrat's primary data holdings consist of regional stratigraphic columns with a spatial footprint weighted heavily to North America. While the data are of sufficient scale and resolution to generate insights about Earth evolution, increasing resolution and expanding spatial coverage will allow a new generation of scientific and interpretive uses. The next phase of Macrostrat's development will increase the detail and complexity of Macrostrat's multiscale data holdings, largely by engaging a wider range of geoscientists in entering stratigraphic data. To support broad collaboration, we are building new web‐based software to assemble and visualize regional stratigraphic sequences, refine multiple working age models, and compose regional records from measured stratigraphic sections. These tools will allow Macrostrat to draw on the expertise of a wide range of geoscience workers and grow a dataset with global relevance and a variety of end uses. New capabilities will pave the way to processes for submission, review, coordination, and assimilation of community‐contributed stratigraphic datasets. Digital compilation of geological maps and columns requires substantial effort, and well‐designed systems for distributing this work in the geoscience community will allow Macrostrat to build more adaptable and scientifically relevant products.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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