NeanderCloud: New and old technologies to understand past human tool technology, design and use
NeanderCloud: New and old technologies to understand past human tool technology, design and use
批准号:
524670940
负责人:
Professor Dr. Andreas Hildebrandt
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:
中文摘要
更新世时期,石器是人类生存的必需品。因此,过去人类技术的出现和变化为早期人类行为提供了基本的见解,并被视为文化特征的结合,也是人类技术适应和创新的结合。了解考古记录中各种各样的石器的生产、设计、功能和实际使用之间的关系,以及它们随时间和空间的变化,是至关重要的。因此,在不同的分析尺度上结合工具设计和使用的研究是至关重要的。这种理解可以对与工具的使用寿命历史相关的问题产生重大影响,包括技术策略,工具维护,重新锐化和回收机制,以及人类决策过程的本质。这些机制只有在工具技术、设计和使用方面结合起来才能解决。虽然这种互补的方法到目前为止还没有在考古研究中实现,尼安德特云项目的目标是在这项调查中取得重大进展。在概念验证研究的基础上,该研究将重点调查中旧石器时代晚期(LMP)不对称工具,即所谓的Keilmesser,以了解它们在中欧和东欧LMP行业中的起源、性质和卓越地位。该项目旨在回答以下问题:•Keilmesser是尼安德特人使用的特定任务工具还是多功能工具?•尼安德特人是否优化了他们的工具设计,或者这是技术文化习俗的结果?•工具设计和使用的不同方面能告诉我们过去人类群体的知识、学习和传播过程吗?通过多尺度分析,本研究旨在结合技术类型学和材料特性研究、使用磨损分析和对照实验等方法,制定一个独特的议程。这种数据组合需要一种统计工具,该工具将为数据分析和数据建模提供透明和可重复的工作流程。在考古研究和计算机科学相互关联的合作基础上,获得的数据将使用深度学习和贝叶斯计算机技术进行建模。由此产生的计算工具,遵循大数据集管理的公平原则,将可供其他研究人员使用。结果将被用作解释考古记录的代理,因此,有助于理解技术行为是如何以及为什么在早期人群中发生的,以及人们如何能够基于他们的技术传统、创新和新奇而生存和繁荣。这将大大有助于认识和解释人类行为的进化和扩展中的不同特征。
英文摘要
During the Pleistocene, stone tools were essential to the survival of hominins. Hence, the emergence and changes of past human technologies provide fundamental insights into early hominin behaviour and have been seen as a combination of cultural traits but also human technological adaptations and innovations. The understanding of the relation between production, design, function, and actual use of the huge variety of stone tools in the archaeological record, and their change over time and space, is fundamental. Therefore, research that combines studies on tool design and use at different scales of analysis are crucial. This understanding can have a major impact on questions related to the use-life history of a tool, including technological strategies, tool maintenance, resharpening and recycling mechanisms, but also on the nature of human decisionmaking processes. These mechanisms can only be addressed when aspects of tool technology, design and use are combined. While such complementary approach has so far not been achieved in archaeological research, the NeanderCloud project aims to achieve major developments in this investigation. Building upon a proof-ofconcept study, the research will focus on the investigation of the Late Middle Palaeolithic (LMP) asymmetric tools, so-called Keilmesser, in order to understand their origin, nature and pre-eminence within the LMP industries in Central and Eastern Europe. This project aims to answer questions such as: • Were Keilmesser task-specific tools or multifunctionally used by Neanderthals? • Did Neanderthals optimise the design of their tools and/or was this a consequence of technocultural conventions? • What can the different aspects of tool design and use tell us about the processes of knowledge, learning and transmission in the past hominin populations? Through a multi-scale analysis this study aims at a unique agenda that combines methods such as techno-typological and material properties studies, use-wear analysis and controlled experiments. This constellation and combination of data requires a statistical tool that will provide a transparent and reproducible workflow for the data analysis and data modelling. Building on an interrelated collaboration between archaeological research and computer science, the obtained data will be modelled using Deep learning and Bayesian computer techniques. The resulting computational tool, following FAIR principles of big data set management, will be available for other researchers. Results will be used as a proxy to interpret the archaeological record, and, therefore, contribute to the understating of how and why technological behaviours took place in earlier populations, and how people were able to survive and thrive based on their technological traditions, innovations, and novelties. This will significantly contribute to the recognition and interpretation of different traits in the evolution and expansion of Human Behaviour.
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HySim: Hybrid-parallel similarity search for the analysis of big genomic and proteomic data
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批准号:329350978
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项目类别:Research Grants
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资助金额:$0.0万
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财政年份:2016
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负责人:Professor Dr. Andreas Hildebrandt
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依托单位:
海外基金