Community Research Education and Engagement for Data Science (CREEDS)

 描述(由申请人提供)：数据丰富的生物医学科学的进展速度受到限制，部分原因是缺乏对大数据集和工具的认识和专业知识，缺乏有效地跨越不同领域的方法，以及劳动力中不同群体的代表性不足。为了解决这些差异，我们提出了信条：社区研究教育和数据科学参与。这个头衔代表着我们致力于为一个全国性的、多样化的、跨学科的早期职业研究人员社区培养实用技能的总体目标。我们的三个具体目标是：(1)为生物医学研究人员提供所需的实用技能和洞察力，以利用大数据科学的力量和前景来加速科学发现；(2)发展在线社交环境，促进新手和专家之间的大数据想法、方法和技术的交流；以及(3)通过有针对性地招聘和留住弱势和代表性不足的学生群体，增强生物医学大数据劳动力的多样性。我们将通过在纽约市举办为期两周的密集、量身定制的暑期班，亲自吸引150名研究生参加，在纽约市各地的学校活动中展示有趣的、最新的合作案例研究。它还将包括负责任的研究行为培训。参与者将使用主动学习技术，通过在现实生活中的大型数据集上的个人和小组任务，发展他们具体的新方法和工具的技能。培训将把不同背景的学生的技能提高到足以进行额外的研究生研究的水平，而不需要任何事先的计算经验。学生们还将获得经验和材料，帮助他们在返回本国机构后教授他人。此外，我们还将指导另外30名纽约的研究生参加为期四个月的梦想挑战。梦想挑战团队将帮助培养解决现实生活中困难的生物医学问题的计算技能。在线社交环境Kipin Hall将使参与者能够发现就业机会，找到数据源和工具，并与同行和大数据专家进行交流。我们将利用我们与服务于代表性不足群体的组织的现有关系来促进参与并加强这一令人兴奋的领域。为了不断改进我们的计划，我们将积极寻求和回应我们的参与者、计划教职员工和我们的顾问小组的反馈。作为这个项目的结果，我们将培训OVR 180人来发展团队技能，以理解、选择和使用基因组数据工具和方法。我们将通过在Coursera上举办暑期班来接触到更多的人。有了这些知识，我们计划下一代基因组科学家将更好地设计、分析和解释高通量基因组数据集。这是研究教育的重要需要，我们的目标是用教义来解决这一问题。

 DESCRIPTION (provided by applicant): The speed of advancement in data-rich biomedical sciences is limited in part by the lack of awareness and expertise in big data sets and tools, the absence of approaches that productively intersect disparate domains, and the underrepresentation of diverse groups in the workforce. To address these disparities, we propose CREEDS: Community Research Education and Engagement for Data Science. This title represents our commitment to our overall goal of fostering practical skills for a national, diverse and interdisciplinary community of early career researchers. Our three specific aims are: (1) to provide biomedical researchers with the practical skills and insight needed to harness the power and advance the promise of big data science to accelerate scientific discovery, (2) to develop an online social environment to facilitate the exchange of big data ideas, approaches and techniques between novices and experts, and (3) to enhance the diversity of the biomedical big data workforce through targeted recruitment and retention of disadvantaged and underrepresented student populations. We will personally engage 150 graduate students through an intensive, self-tailored, two-week summer school in NYC that will showcase interesting, and current, collaborative case studies in activities at schools throughout NYC. It wil also include training in the Responsible Conduct of Research. Participants will employ active learning techniques to develop their skills of specific new methods and tools through both individual and group tasks on real-life large data sets. The training will raise the skills of students of varied backgrounds to a sufficient level for additional graduate research and will not require any prior computing experience. Students will also receive experience and materials to help them teach others when they return to their home institutions. Additionally, we will mentor another 30 NYC-based graduate students for team participation in four month long DREAM challenges. The DREAM challenge teams will help develop computational skills on solving difficult, real-life biomedical problems. An online social environment, Kipin Hall, will enable participants to discover job opportunities, find data sources and tools and communicate with peers as well as big data experts. We will leverage our extant relationships with organizations serving underrepresented groups to boost participation and enhance this exciting field. To continually improve our program we will actively seek and respond to feedback from our participants, program faculty and our advisory panel. As a result of this project, we will train ovr 180 people to develop team skills to understand, select and use genomics data tools and approaches. We will reach more individuals by placing the summer school on Coursera. Armed with this knowledge, we plan that the next generation of genomics scientists will be better placed to design, analyze and interpret high-throughput genomics datasets. This is the important need for research education that we aim to address with CREEDS.