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These are the 39 sites and distance between them used in a series of papers by T.S.Evans, C.Knappett and R.J.Rivers. They represent major centres in the Middle Bronze age of the Aegean (era of Minoan civilisation). Information on these excel files and on some of the papers using this data is contained in a pdf or can be found following the links provided. I also provide figures shwoing the location of these sites along with a QGIS project file used to create the figures. These are the 39 sites and distance between them used in a series of papers by T.S.Evans, C.Knappett and R.J.Rivers. They represent major centres in the Middle Bronze age of the Aegean (era of Minoan civilisation). Information on these excel files and on some of the papers using this data is contained in a pdf or can be found following the links provided. I also provide figures shwoing the location of these sites along with a QGIS project file used to create the figures. These are the 39 sites and distance between them used in a series of papers by T.S.Evans, C.Knappett and R.J.Rivers. They represent major centres in the Middle Bronze age of the Aegean (era of Minoan civilisation). Information on these excel files and on some of the papers using this data is contained in a pdf or can be found following the links provided. I also provide figures shwoing the location of these sites along with a QGIS project file used to create the figures.

Locations of Archaeic Greek settlements used in RW87 T. E. Rihll and A. G. Wilson, “Spatial Interaction and Structural Models in Historical Analysis: Some Possibilities and an Example” in Histoire & Mesure, 1987 volume 2 - n°1. pp. 5-32. These are derived from a digitisation of Figure 1 of RW87. If you find these useful, please cite this figshare archive or T.S.Evans, R.J.Rivers, New approaches to Archaic Greek settlement structure , to appear in Les Nouvelles de l’Archéologie, 2014. Locations of Archaeic Greek settlements used in RW87 T. E. Rihll and A. G. Wilson, “Spatial Interaction and Structural Models in Historical Analysis: Some Possibilities and an Example” in Histoire & Mesure, 1987 volume 2 - n°1. pp. 5-32. These are derived from a digitisation of Figure 1 of RW87. If you find these useful, please cite this figshare archive or T.S.Evans, R.J.Rivers, "New approaches to Archaic Greek settlement structure", to appear in Les Nouvelles de l’Archéologie, 2014. Locations of Archaeic Greek settlements used in RW87 T. E. Rihll and A. G. Wilson, “Spatial Interaction and Structural Models in Historical Analysis: Some Possibilities and an Example” in Histoire & Mesure, 1987 volume 2 - n°1. pp. 5-32. These are derived from a digitisation of Figure 1 of RW87. If you find these useful, please cite this figshare archive or T.S.Evans, R.J.Rivers, "New approaches to Archaic Greek settlement structure", to appear in Les Nouvelles de l’Archéologie, 2014.

Background information, figures and most tables used for:- Evans, T.S. (2014). ‘Which Network Model Should I Use? Towards a Quantitative Comparison of Spatial Network Models in Archaeology’, in T. Brughmans, A. Collar and F. Coward (eds), The Connected Past: challenging networks in archaeology and history. Cambridge: Cambridge University Press, chapter 8. The files contain the figures and most of the tables used in the paper. Background information on the programmes used and on their input data also here e.g. the locations of the 40 test sites used in the paper (shown in figure 5). More details about these files are in the file InformationOnFiles.pdf. Background information, figures and most tables used for:- Evans, T.S. (2014). ‘Which Network Model Should I Use? Towards a Quantitative Comparison of Spatial Network Models in Archaeology’, in T. Brughmans, A. Collar and F. Coward (eds), The Connected Past: challenging networks in archaeology and history. Cambridge: Cambridge University Press, chapter 8. The files contain the figures and most of the tables used in the paper. Background information on the programmes used and on their input data also here e.g. the locations of the 40 test sites used in the paper (shown in figure 5). More details about these files are in the file InformationOnFiles.pdf. Background information, figures and most tables used for:- Evans, T.S. (2014). ‘Which Network Model Should I Use? Towards a Quantitative Comparison of Spatial Network Models in Archaeology’, in T. Brughmans, A. Collar and F. Coward (eds), The Connected Past: challenging networks in archaeology and history. Cambridge: Cambridge University Press, chapter 8. The files contain the figures and most of the tables used in the paper. Background information on the programmes used and on their input data also here e.g. the locations of the 40 test sites used in the paper (shown in figure 5). More details about these files are in the file InformationOnFiles.pdf.

This is the example MultiNest chain from arXiv:0909.3300, used in the pippi example, and referred to in the pippi paper and documentation.

A collection of material associated with The Connected Past London 2014, a one and a half day multi-disciplinary meeting held at Imperial College on the 8th and 9th of September, 2014 and attended by nearly fifty researchers. It aims to explore how concepts and techniques from network- and complexity science can be used to study archaeological and historical data. It is part of a series of meetings organised by The Connected Past team. Slides from most (but not all) talks are provided. Most talks were also recorded but the videos are yet to be made available. A collection of material associated with The Connected Past London 2014, a one and a half day multi-disciplinary meeting held at Imperial College on the 8th and 9th of September, 2014 and attended by nearly fifty researchers. It aims to explore how concepts and techniques from network- and complexity science can be used to study archaeological and historical data. It is part of a series of meetings organised by The Connected Past team. Slides from most (but not all) talks are provided. Most talks were also recorded but the videos are yet to be made available. A collection of material associated with The Connected Past London 2014, a one and a half day multi-disciplinary meeting held at Imperial College on the 8th and 9th of September, 2014 and attended by nearly fifty researchers. It aims to explore how concepts and techniques from network- and complexity science can be used to study archaeological and historical data. It is part of a series of meetings organised by The Connected Past team. Slides from most (but not all) talks are provided. Most talks were also recorded but the videos are yet to be made available.

This study comprises meter reading and consumer survey data from the UK's first residential sector, dynamic time-of-use electricity pricing trial, which took place as part of the Low Carbon London (LCL) project. The trial involved 5,567 households in the London area, of which 1,122 received an experimental dynamic time-of-use (dToU) tariff, which was in effect for the duration of 2013. The Low Carbon London project was a £28m research programme that ran from the beginning of 2011 to the end of 2014 and was funded by energy consumers via Ofgem's Low Carbon Network Fund. The programme was designed to investigate the impact of a wide range of low carbon technologies on London's electricity distribution network. It was in this context that the UK's first residential sector, dynamic electricity-pricing trial took place. The trial was carried out by a partnership of organisations: UK Power Networks, the London DNO and the lead programme partner; Imperial College London, responsible for trial design and results analysis; EDF Energy, retail energy supplier and implementer of the dToU tariff; Siemens, responsible for database and communications implementation; and Logica (now CGI), the smart meter head-end. The learning objectives of the trial were twofold: to understand the potential value of dynamic pricing to the electricity system, and to understand its social impact on residential consumers. This study comprises meter reading and consumer survey data from the UKs first residential sector, dynamic time-of-use electricity pricing trial, which took place as part of the Low Carbon London (LCL) project. The trial involved 5,567 households in the London area, of which 1,122 received an experimental dynamic time-of-use (dToU) tariff, which was in effect for the duration of 2013. The Low Carbon London project was a £28m research programme that ran from the beginning of 2011 to the end of 2014 and was funded by energy consumers via Ofgems Low Carbon Network Fund. The programme was designed to investigate the impact of a wide range of low carbon technologies on Londons electricity distribution network. It was in this context that the UKs first residential sector, dynamic electricity-pricing trial took place. The trial was carried out by a partnership of organisations: UK Power Networks, the London DNO and the lead programme partner; Imperial College London, responsible for trial design and results analysis; EDF Energy, retail energy supplier and implementer of the dToU tariff; Siemens, responsible for database and communications implementation; and Logica (now CGI), the smart meter head-end. The learning objectives of the trial were twofold: to understand the potential value of dynamic pricing to the electricity system, and to understand its social impact on residential consumers.

Talk presented at NetSci-X, Wrocław, 12th January 2016.Models of the citation distribution of academic papers have a long history (Price, 1965). One aim is to illustrate if certain simple processes can explain important features. In this paper we focus on the fact that the distribution of citations for papers of a similar age scales primarily with the average number of citations (Radicchi, Fortunato, & Castellano 2008, Evans, Hopkins & Kaube, 2012), with the shape otherwise largely invariant. In particular the width of such distributions (as measured by the s parameter of a lognormal fit to reasonably well cited papers) shows no temporal evolution. Simple multiplicative processes or basic models such as the Price model (Price 1965) give dramatically different results, typically the distributions become narrower over time. We found that to get a reasonable agreement our model had to incorporate three key aspects: local searches of the network (these generate preferential attachment), such local searches had to start from recent papers, and finally some knowledge of the global set of papers was needed. from recent papers, plus global access to papers, we needed. To check our results we used data from the citation network of the hep-th section of the arXiv repository (KDD cup 2003) as a benchmark. Our three-parameter model was able to produce an acceptable fit to the hep-th data over 11 different years (see figure). We find the best fits for our model to our data is when around 70% to 80% of papers cited are ‘subsidiary papers’, papers found from local searches through the bibliographies of other papers. Interestingly similar results have been seen by Simkin and Roychowdhury (2005) derived from an analysis of mistakes in bibliographic entries. In our terminology these would be citations to subsidiary papers so both sets of results are consistent. Further support for this result comes from the transitive reduction analysis of Clough et al. (2015). We conclude that the citation patterns we see are based on around 25% of papers found from some global source come from reflect a mixture of local searches from papers found through some global information but favouring recent papers, with the remainder then found by local searches. Talk presented at NetSci-X, Wrocław, 12th January 2016.Models of the citation distribution of academic papers have a long history (Price, 1965). One aim is to illustrate if certain simple processes can explain important features. In this paper we focus on the fact that the distribution of citations for papers of a similar age scales primarily with the average number of citations (Radicchi, Fortunato, & Castellano 2008, Evans, Hopkins & Kaube, 2012), with the shape otherwise largely invariant. In particular the width of such distributions (as measured by the s parameter of a lognormal fit to reasonably well cited papers) shows no temporal evolution. Simple multiplicative processes or basic models such as the Price model (Price 1965) give dramatically different results, typically the distributions become narrower over time. We found that to get a reasonable agreement our model had to incorporate three key aspects: local searches of the network (these generate preferential attachment), such local searches had to start from recent papers, and finally some knowledge of the global set of papers was needed. from recent papers, plus global access to papers, we needed. To check our results we used data from the citation network of the hep-th section of the arXiv repository (KDD cup 2003) as a benchmark. Our three-parameter model was able to produce an acceptable fit to the hep-th data over 11 different years (see figure). We find the best fits for our model to our data is when around 70% to 80% of papers cited are ‘subsidiary papers’, papers found from local searches through the bibliographies of other papers. Interestingly similar results have been seen by Simkin and Roychowdhury (2005) derived from an analysis of mistakes in bibliographic entries. In our terminology these would be citations to subsidiary papers so both sets of results are consistent. Further support for this result comes from the transitive reduction analysis of Clough et al. (2015). We conclude that the citation patterns we see are based on around 25% of papers found from some global source come from reflect a mixture of local searches from papers found through some global information but favouring recent papers, with the remainder then found by local searches. Talk presented at NetSci-X, Wrocław, 12th January 2016.Models of the citation distribution of academic papers have a long history (Price, 1965). One aim is to illustrate if certain simple processes can explain important features. In this paper we focus on the fact that the distribution of citations for papers of a similar age scales primarily with the average number of citations (Radicchi, Fortunato, & Castellano 2008, Evans, Hopkins & Kaube, 2012), with the shape otherwise largely invariant. In particular the width of such distributions (as measured by the s parameter of a lognormal fit to reasonably well cited papers) shows no temporal evolution. Simple multiplicative processes or basic models such as the Price model (Price 1965) give dramatically different results, typically the distributions become narrower over time. We found that to get a reasonable agreement our model had to incorporate three key aspects: local searches of the network (these generate preferential attachment), such local searches had to start from recent papers, and finally some knowledge of the global set of papers was needed. from recent papers, plus global access to papers, we needed. To check our results we used data from the citation network of the hep-th section of the arXiv repository (KDD cup 2003) as a benchmark. Our three-parameter model was able to produce an acceptable fit to the hep-th data over 11 different years (see figure). We find the best fits for our model to our data is when around 70% to 80% of papers cited are ‘subsidiary papers’, papers found from local searches through the bibliographies of other papers. Interestingly similar results have been seen by Simkin and Roychowdhury (2005) derived from an analysis of mistakes in bibliographic entries. In our terminology these would be citations to subsidiary papers so both sets of results are consistent. Further support for this result comes from the transitive reduction analysis of Clough et al. (2015). We conclude that the citation patterns we see are based on around 25% of papers found from some global source come from reflect a mixture of local searches from papers found through some global information but favouring recent papers, with the remainder then found by local searches.