With the proliferation of online learning, the future of classroom teaching has been called into question. However, the unfaltering popularity of brick-and-mortar courses indicates that direct access to expert knowledge and face-to-face engagements remain key considerations for students. Here we showcase a combination of these two worlds in a Small Private Online Course (SPOC). Compared to Massive Open Online Courses (MOOCs), SPOCs are developed for smaller and more dedicated target groups and depend on close engagement between teachers and students. This format enables educational providers to involve internal and external students and teachers alike and to make ample use of online resources. This paper is based upon our experiences of running a SPOC on ‘Modelling and Simulation in Archaeology’ at Leiden University. We review the process of developing and running the course aimed at teaching archaeology students computer programming skills, while supporting their development as professional archaeologists and responsible academics.
{"title":"Digitally Teaching Digital Skills: Lessons Drawn from a Small Private Online Course (SPOC) on ‘Modelling and Simulation in Archaeology’ at Leiden University","authors":"F. Scherjon, I. Romanowska, K. Lambers","doi":"10.5334/JCAA.26","DOIUrl":"https://doi.org/10.5334/JCAA.26","url":null,"abstract":"With the proliferation of online learning, the future of classroom teaching has been called into question. However, the unfaltering popularity of brick-and-mortar courses indicates that direct access to expert knowledge and face-to-face engagements remain key considerations for students. Here we showcase a combination of these two worlds in a Small Private Online Course (SPOC). Compared to Massive Open Online Courses (MOOCs), SPOCs are developed for smaller and more dedicated target groups and depend on close engagement between teachers and students. This format enables educational providers to involve internal and external students and teachers alike and to make ample use of online resources. This paper is based upon our experiences of running a SPOC on ‘Modelling and Simulation in Archaeology’ at Leiden University. We review the process of developing and running the course aimed at teaching archaeology students computer programming skills, while supporting their development as professional archaeologists and responsible academics.","PeriodicalId":32632,"journal":{"name":"Journal of Computer Applications in Archaeology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42764719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A critical aspect of analysing an archaeological site is identifying the network of relationships between the things we find and the locations where we find them. These associations are typically determined by a combination of quantitative analyses and the professional knowledge and intuition of the archaeologist, but where exactly is the boundary between what is truly empirical field data and what is inferred through our prior knowledge and field methods? How can we best support those inferences? This paper is a critical evaluation of that boundary to firmly ground, as much as possible, a quantitative analysis on only that which we can directly observe – the thing and its location – and derive associations from that basis alone. To do so, the approach described here relies on a combination of set and graph theories rather than statistical or spatial methods. This revised ontology allows a formalization, in combinatorial terms, for describing an underlying structure to contexts and assemblages that suggests a clear association between archaeological site analysis and a well-studied class of set and graph covering problems. This, in turn, points towards potential algorithmic solutions for a more holistic parsing of the total relationships between sites, contexts, assemblages, proveniences, and artefacts.
{"title":"Sets, Graphs, and Things We Can See: A Formal Combinatorial Ontology for Empirical Intra-Site Analysis","authors":"J. Cardinal","doi":"10.5334/JCAA.16","DOIUrl":"https://doi.org/10.5334/JCAA.16","url":null,"abstract":"A critical aspect of analysing an archaeological site is identifying the network of relationships between the things we find and the locations where we find them. These associations are typically determined by a combination of quantitative analyses and the professional knowledge and intuition of the archaeologist, but where exactly is the boundary between what is truly empirical field data and what is inferred through our prior knowledge and field methods? How can we best support those inferences? This paper is a critical evaluation of that boundary to firmly ground, as much as possible, a quantitative analysis on only that which we can directly observe – the thing and its location – and derive associations from that basis alone. To do so, the approach described here relies on a combination of set and graph theories rather than statistical or spatial methods. This revised ontology allows a formalization, in combinatorial terms, for describing an underlying structure to contexts and assemblages that suggests a clear association between archaeological site analysis and a well-studied class of set and graph covering problems. This, in turn, points towards potential algorithmic solutions for a more holistic parsing of the total relationships between sites, contexts, assemblages, proveniences, and artefacts.","PeriodicalId":32632,"journal":{"name":"Journal of Computer Applications in Archaeology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42744461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study uses data extracted from 3D models to compare blade cores from the Châtelperronian and Protoaurignacian stone tool industries. These technocomplexes are at the center of the debate surrounding the interactions between Neanderthals and anatomically modern humans approximately 45 to 40,000 years ago. We created 3D models of lithic cores from the sites of Roc de Combe and Les Cottes using a standardized photogrammetry protocol. We then used data derived from these 3D models to make quantitative comparisons of artifact attributes that have previously been argued to distinguish the two stone tool industries in question. These attributes include the angle between the platform and flaking surfaces, the shape of core cross sections, and the angle between core axes. The conception of this study was not to privilege the use of new technological and statistical approaches over more traditional or qualitative forms of lithic analysis. Rather, our aim was to experiment with using digital tool to develop nuanced, reproducible ways to describe variability in lithic artifacts. Our results support the hypothesis that there is a difference in the angle between core surfaces between these two industries. Our analysis also indicates a difference in the angle between core axes, although we are more cautious in interpreting these results. An elliptical Fourier analysis of core cross section shape was inconclusive. We discuss what archaeological and methodological factors may have contributed to our results, and the roles of both qualitative and quantitative observations in archaeological research. 3D artifact models generated for this study are included as supplemental data and are available for use by other researchers.
这项研究使用从3D模型中提取的数据来比较Châtelperronian和Protauriganian石器行业的刀片芯。这些技术复合体是围绕大约45至40000年前尼安德特人和解剖学上的现代人类之间相互作用的争论的中心。我们使用标准化摄影测量协议创建了Roc de Combe和Les Cottes遗址的石器时代岩芯的3D模型。然后，我们使用从这些3D模型中获得的数据对人工制品属性进行定量比较，这些属性以前被认为是区分这两个有问题的石器行业的依据。这些属性包括平台和剥落表面之间的角度、芯横截面的形状以及芯轴之间的角度。这项研究的概念并不是要优先使用新的技术和统计方法，而不是更传统或定性的石器分析形式。相反，我们的目标是尝试使用数字工具来开发细致入微、可重复的方法来描述石器时代文物的可变性。我们的研究结果支持这样一种假设，即这两个行业的核心表面之间的角度存在差异。我们的分析还表明，核心轴之间的角度存在差异，尽管我们在解释这些结果时更加谨慎。芯横截面形状的椭圆傅立叶分析没有结论。我们讨论了哪些考古和方法因素可能对我们的结果有贡献，以及定性和定量观察在考古研究中的作用。为这项研究生成的3D伪影模型作为补充数据，可供其他研究人员使用。
{"title":"A Comparison of Châtelperronian and Protoaurignacian Core Technology Using Data Derived from 3D Models","authors":"Samantha T Porter, Morgan Roussel, M. Soressi","doi":"10.5334/JCAA.17","DOIUrl":"https://doi.org/10.5334/JCAA.17","url":null,"abstract":"This study uses data extracted from 3D models to compare blade cores from the Châtelperronian and Protoaurignacian stone tool industries. These technocomplexes are at the center of the debate surrounding the interactions between Neanderthals and anatomically modern humans approximately 45 to 40,000 years ago. We created 3D models of lithic cores from the sites of Roc de Combe and Les Cottes using a standardized photogrammetry protocol. We then used data derived from these 3D models to make quantitative comparisons of artifact attributes that have previously been argued to distinguish the two stone tool industries in question. These attributes include the angle between the platform and flaking surfaces, the shape of core cross sections, and the angle between core axes. The conception of this study was not to privilege the use of new technological and statistical approaches over more traditional or qualitative forms of lithic analysis. Rather, our aim was to experiment with using digital tool to develop nuanced, reproducible ways to describe variability in lithic artifacts. Our results support the hypothesis that there is a difference in the angle between core surfaces between these two industries. Our analysis also indicates a difference in the angle between core axes, although we are more cautious in interpreting these results. An elliptical Fourier analysis of core cross section shape was inconclusive. We discuss what archaeological and methodological factors may have contributed to our results, and the roles of both qualitative and quantitative observations in archaeological research. 3D artifact models generated for this study are included as supplemental data and are available for use by other researchers.","PeriodicalId":32632,"journal":{"name":"Journal of Computer Applications in Archaeology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49489332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Computer-aided methods for the automatic detection of archaeological objects are needed to cope with the ever-growing set of largely digital and easily available remotely sensed data. In this paper, a promising new technique for the automated detection of multiple classes of archaeological objects in LiDAR data is presented. This technique is based on R-CNNs (Regions-based Convolutional Neural Networks). Unlike normal CNNs, which classify the entire input image, R-CNNs address the problem of object detection, which requires correctly localising and classifying (multiple) objects within a larger image. We have incorporated this technique into a workflow, which enables the preprocessing of LiDAR data into the required data format and the conversion of the results of the object detection into geographical data, usable in a GIS environment. The proposed technique has been trained and tested on LiDAR data gathered from the central part of the Netherlands. This area contains a multitude of archaeological objects, including prehistoric barrows and Celtic fields. The initial experiments show that we are able to automatically detect and categorise these two types of archaeological objects and thus proof the added value of this technique.
{"title":"Learning to Look at LiDAR: The Use of R-CNN in the Automated Detection of Archaeological Objects in LiDAR Data from the Netherlands","authors":"Wouter B. Verschoof‐van der Vaart, K. Lambers","doi":"10.5334/JCAA.32","DOIUrl":"https://doi.org/10.5334/JCAA.32","url":null,"abstract":"Computer-aided methods for the automatic detection of archaeological objects are needed to cope with the ever-growing set of largely digital and easily available remotely sensed data. In this paper, a promising new technique for the automated detection of multiple classes of archaeological objects in LiDAR data is presented. This technique is based on R-CNNs (Regions-based Convolutional Neural Networks). Unlike normal CNNs, which classify the entire input image, R-CNNs address the problem of object detection, which requires correctly localising and classifying (multiple) objects within a larger image. We have incorporated this technique into a workflow, which enables the preprocessing of LiDAR data into the required data format and the conversion of the results of the object detection into geographical data, usable in a GIS environment. The proposed technique has been trained and tested on LiDAR data gathered from the central part of the Netherlands. This area contains a multitude of archaeological objects, including prehistoric barrows and Celtic fields. The initial experiments show that we are able to automatically detect and categorise these two types of archaeological objects and thus proof the added value of this technique.","PeriodicalId":32632,"journal":{"name":"Journal of Computer Applications in Archaeology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45111601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alex Brandsen, K. Lambers, S. Verberne, M. Wansleeben
In this paper, we present the results of user requirement solicitation for a search system of grey literature in archaeology, specifically Dutch excavation reports. This search system uses Named Entity Recognition and Information Retrieval techniques to create an effective and effortless search experience. Specifically, we used Conditional Random Fields to identify entities, with an average accuracy of 56%. This is a baseline result, and we identified many possibilities for improvement. These entities were indexed in ElasticSearch and a user interface was developed on top of the index. This proof of concept was used in user requirement solicitation and evaluation with a group of end users. Feedback from this group indicated that there is a dire need for such a system, and that the first results are promising.
{"title":"User Requirement Solicitation for an Information Retrieval System Applied to Dutch Grey Literature in the Archaeology Domain","authors":"Alex Brandsen, K. Lambers, S. Verberne, M. Wansleeben","doi":"10.5334/JCAA.33","DOIUrl":"https://doi.org/10.5334/JCAA.33","url":null,"abstract":"In this paper, we present the results of user requirement solicitation for a search system of grey literature in archaeology, specifically Dutch excavation reports. This search system uses Named Entity Recognition and Information Retrieval techniques to create an effective and effortless search experience. Specifically, we used Conditional Random Fields to identify entities, with an average accuracy of 56%. This is a baseline result, and we identified many possibilities for improvement. These entities were indexed in ElasticSearch and a user interface was developed on top of the index. This proof of concept was used in user requirement solicitation and evaluation with a group of end users. Feedback from this group indicated that there is a dire need for such a system, and that the first results are promising.","PeriodicalId":32632,"journal":{"name":"Journal of Computer Applications in Archaeology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42513472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Game engines are developing fast and are used in several scientific disciplines. In the domain of cultural heritage, they have been applied mostly for dynamic visualization. On the other hand, GISs are employed to address research questions with a spatial component. In an ideal situation, the visualization power and analytical strength of the two technologies should be combined in one system. With this in mind, the analytical potential of a game engine was investigated based on a comparison with GIS analysis of historical routes. The outcome demonstrates the suitability of the game engine in offering extra analytical possibilities. This analytical capacity encourages further script developments in building more historically accurate models.
{"title":"First Steps in the Use of a Game Engine for Historical Roads and Paths Research","authors":"W. Vletter","doi":"10.5334/JCAA.18","DOIUrl":"https://doi.org/10.5334/JCAA.18","url":null,"abstract":"Game engines are developing fast and are used in several scientific disciplines. In the domain of cultural heritage, they have been applied mostly for dynamic visualization. On the other hand, GISs are employed to address research questions with a spatial component. In an ideal situation, the visualization power and analytical strength of the two technologies should be combined in one system. With this in mind, the analytical potential of a game engine was investigated based on a comparison with GIS analysis of historical routes. The outcome demonstrates the suitability of the game engine in offering extra analytical possibilities. This analytical capacity encourages further script developments in building more historically accurate models.","PeriodicalId":32632,"journal":{"name":"Journal of Computer Applications in Archaeology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49282786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article details a correction to the article: Huggett, J., Reilly, P. and Lock, G., 2018. Whither Digital Archaeological Knowledge? The Challenge of Unstable Futures. Journal of Computer Applications in Archaeology, 1(1), pp. 42–54. DOI: https://doi.org/10.5334/jcaa.7 .
{"title":"Correction: Whither Digital Archaeological Knowledge? The Challenge of Unstable Futures","authors":"J. Huggett, P. Reilly, G. Lock","doi":"10.5334/JCAA.21","DOIUrl":"https://doi.org/10.5334/JCAA.21","url":null,"abstract":"This article details a correction to the article: Huggett, J., Reilly, P. and Lock, G., 2018. Whither Digital Archaeological Knowledge? The Challenge of Unstable Futures. Journal of Computer Applications in Archaeology, 1(1), pp. 42–54. DOI: https://doi.org/10.5334/jcaa.7 .","PeriodicalId":32632,"journal":{"name":"Journal of Computer Applications in Archaeology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43418115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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