Systems Archaeology Research Group
“Perhaps the search for regularities in human history is becoming a trifle more respectable than it was formerly. That could well portend some significant improvement in our ability to discuss the human future.” Murray Gell-Mann, recipient of the Physics Nobel Prize & co-founder of the Santa Fe Institute
In the quest for Gell-Mann’s vision, the Systems Archaeology research group is developing the field of Historical Science based on dynamical systems theory. We employ interdisciplinary methods to accurately and precisely describe past human activities and their environmental contexts across space and time. Modelling applied to large amounts of diverse paleo-data is then used to investigate the causal mechanisms behind past societal dynamics. Our ultimate goal is to produce historical knowledge that can be usefully employed by risk analysts and policymakers tackling present-day collective challenges. Currently, we pursue the following research topics:
- Human agency in complex dynamical systems
- Emergence and impact of technological innovations
- Formation of networks for the exchange of materials and information
- The rise and demise of past societies
- Feedback mechanisms among human, environmental, and climatic systems
- Interplay between socioeconomic inequality and societal dynamics
A structural activity of our research group is the advancement of Big Historical Data following FAIR and CARE principles via the Pandora & IsoMemo initiatives. Another component of these initiatives is the development of advanced open-source modelling tools to reconstruct various aspects of past human-environmental systems and to investigate historical causation (further details below under Pandora & IsoMemo project). This work is carried out under the Computational Archaeology lab (CA lab) and in collaboration with several international institutions.
Our research group also produces new data. We oversee the running of the Radiocarbon lab (14C lab), a clean wet chemistry facility hosting a Ionplus AGE 3 automated graphitization equipment and portable XRF and FTIR devices to assess sample preservation. In collaboration with the AMS facility of the Max Planck Institute for Biogeochemistry we employ radiocarbon to set the chronologies of past events and as a tracer to investigate a variety of environmental phenomena. We co-manage, together with the Biochemistry research group, the Compound Specific Isotopic Analysis lab (CSIA lab) equipped with a Gas Chromatography Combustion Isotope Ratio Mass Spectrometer (elementar isoprime visION System). In collaboration with the Stable isotope group, we employ isotopic methods to study past societies and environments and we carry out fundamental research to expand their range of applications.
Pandora & IsoMemo Initiatives for Big Historical Data Compilation and Modelling
Project members: Sean Hixon, Carlo Cocozza, Marcus Groß, Jian Roachell, Traci N Billings, Adam Izdebski, Patrick Roberts, Ricardo Fernandes
An effective understanding of past historical dynamics under a systems approach requires large volumes of diverse data. This should be structured as linked open data so that different systems’ components can be efficiently connected. To achieve this, we developed the Pandora data platform in collaboration with the Max Planck Computing and Data Facility and the Max Planck Library plus c. 60 international partners. Pandora is a grassroots initiative promoting the creation of independently managed data communities and wider collaborative data networks. Among these is the IsoMemo network connecting c. 40 open-access databases that compile isotopic data informing on the environmental history of the Earth and of its human inhabitants from the deep past until the present day. Amassed data via Pandora is used to test historical hypotheses and in data-driven approaches that seek to identify historical patterns.
We are also developing novel R modelling tools for historical research. These are made available online via the Pandora & IsoMemo open-source software platform and are designed to address typical aspects of historical data such as missing data, data uncertainties, and reliance on expert information. We employ Bayesian modelling of proxy data and expert inputs to produce high-resolution reconstructions of various aspects that characterized past human-environmental systems. Machine learning techniques, such as Bayesian networks and non-linear model selection algorithms, are used to study historical causation. We develop and/or collaborate in the development of models and software to investigate various aspects of complex systems such as the study of cyclical human and environmental phenomena, detection of critical transitions and their warning signs, simulation of emerging phenomena using agent-based modelling, and in network analysis.
The Pandora & IsoMemo initiatives are also involved in direct data collection efforts although this is mostly carried out by network members. There are several research projects underway that apply newly developed modelling tools to compiled datasets. This includes projects investigating the spread of peoples, domesticates, and technologies at continental scales; determining the causes of species extinction; and surveying un/successful human adaptions to climate change.
Using Artificial Intelligence to Track, Compile, and Model Expert Information
Project Members: Jian Rochell, Ricardo Fernandes
We are facing an overflow of scientific information. Ideally the design of a model should evaluate all available data across published records that may be used to describe its different components. For historical research this is highly dependent on expert opinions that condense a variety of data using text descriptions. However, the compilation of this type of knowledge by individual researchers is becoming increasingly difficult given the large volume of scientific literature and its rapid growth. To address this issue, we are introducing artificial intelligence (AI) methods in collaboration with the Max Planck Library and IBM to automate the process of tracking and extracting expert evidence from written publications. The AI system is capable of locating expert statements for a selected topic and generates a narrative review of pro/con arguments. We plan to use the AI system to assess expert consensus, validate level of expertise, and automatically incorporate expert evidence into historical models.
A Systems Approach to the Study of the Collapse of the Western Roman Empire
Project members: Jian Rochell, Ricardo Fernandes
The collapse of the Western Roman Empire has long been a subject of scholarly research and of public interest. Yet, the exact causes behind the collapse still elude us. Famously, Alexander Demandt enumerated 210 different collapse causes from published literature. In revisiting this topic, we employ a multivariate approach based on complex systems theory that considers the interactions among various human-environmental sub-systems (e.g. socio-economic, political, cultural, technological, environmental, and climatic). To characterize past systems we collect and standardize previously published data plus carry out new data collections. Novel modelling methods for the study of historical causation will be applied to amassed data. In the future, we plan to employ similar approaches in the study of other past societies.
Human Lifeways in the Ancient Mediterranean and its Periphery
Project members: Carlo Cocozza, Dominika Schmidtová, Linda Melicherová, Ricardo Fernandes
In recent years the Mediterranean region has been a focal point in international affairs as economic crashes, armed conflicts, and dwindling natural resources triggered by climate change have resulted in a wide range of responses from mild social unrest to large-scale humanitarian crises and mass migrations. Such issues are not new and Mediterranean societies experienced throughout their history the consequences of climatic, environmental, pandemic, and armed conflict events. The goal of this project is to improve our understanding of the repercussions that such events had on the lifeways of ancient populations in the Mediterranean region and its periphery. We employ multi-proxy approaches (e.g. isotopes, osteological analyses, archaeofaunal and archaeobotanical studies) and Bayesian modelling to reconstruct the living conditions and productive activities of past populations and to set these in their historical and environmental contexts. The project relies on novel site studies (e.g. Sparta, Athens, Rome, Ostia, Pompeii, and Persepolis) and on standardized compilations of published data.
Developing Multi-isotope Methods for the Study of Past Human-Environmental Systems
Project members: Sean Hixon, Ricardo Fernandes
Our research group produces novel historical and paleo-environmental data via the Radiocarbon and the Compound Specific Isotopic Analysis laboratories. The latter is under a joint directorship with the Biochemistry research group and the former is part of a collaboration with the AMS laboratory of the Max Planck Institute for Biogeochemistry. Isotopes are an eclectic research tool used to set chronologies and to investigate past human living conditions, economic activities, exchange networks, technological developments, and paleo-environmental and -climatic conditions. Fundamental research is undertaken to widen the range of information that can be obtained using isotopic methods, improve the accuracy and precision of paleo-reconstructions, and ensure the protection of cultural heritage. We develop novel lab protocols to be applied in the analysis of archaeological samples, set up procedures to determine sample preservation using portable FTIR and XRF devices, and rely on advanced mass spectrometry techniques to produce measurements for a variety of isotopic proxies.