Datasets produced from Dimensions on Google BigQuery regarding the movement of the centre of mass of global publication. Four datasets are contained:1) The number of affiliations in the Dimensions dataset associated with GRID (http://grid.ac) on a yearly basis2) The centre of mass of global publication output, year by year, unweighted3) The centre of mass of global publication output, year by year, weighted by citation
4) The centre of mass of global COVID-19 publication output, month by month in 2020, weighted by citation

Datasets produced from Dimensions on Google BigQuery regarding the movement of the centre of mass of global publication. Four datasets are contained:1) The number of affiliations in the Dimensions dataset associated with GRID (http://grid.ac) on a yearly basis2) The centre of mass of global publication output, year by year, unweighted3) The centre of mass of global publication output, year by year, weighted by citation
4) The centre of mass of global COVID-19 publication output, month by month in 2020, weighted by citation

The data describe a two aspects of an "academic genealogy". The supervisor of a doctoral thesis candidate is often thought of as the intellectual parent of the candidate. Modelling the relationship between students and their supervisors is often done. This is the first aspect of this dataset. The second aspect that we have included in this dataset is a weaker link - that of the role played by the examiner of the student. From the files included here it is possible to create a hierarchical, directed (time-based) network describing the genealogy of primatologists. Data includes the institutional affiliations of all parties at the time of the key activity (either supervision or examination).

The data describe a two aspects of an "academic genealogy". The supervisor of a doctoral thesis candidate is often thought of as the intellectual parent of the candidate. Modelling the relationship between students and their supervisors is often done. This is the first aspect of this dataset. The second aspect that we have included in this dataset is a weaker link - that of the role played by the examiner of the student. From the files included here it is possible to create a hierarchical, directed (time-based) network describing the genealogy of primatologists. Data includes the institutional affiliations of all parties at the time of the key activity (either supervision or examination).

This file contains a set of eigenvalues obtained by solving the eigenvalue problem associated with the differential equation $-\frac{\partial^2 \psi}{\partial x^2}+x^2(i x)^\epsilon\psi=E\psi$. The method of solution is numerical in nature using Mathematica 9's built in NDSolve function with a 9th order adaptive Runge-Kutta method and a standardized shooting algorithm. All eigenvalues are quoted to 6 places and have been calculated to higher precision in order to ensure 6 valid places. This problem was oringally solved and published under: Real Spectra in Non-Hermitian Hamiltonians Having PT Symmetry by Carl M Bender and Stefan Boettcher [Phys.Rev.Lett. 80 (1998) 5243-5246]. This dataset demonstrates independent reproduction of the original results and makes the data underlying the figures in the paper available to those who wish to check their own results. Further eigenvalues and supporting information to follow in this dataset [DWH - 14/2/2013].

This file contains a set of eigenvalues obtained by solving the eigenvalue problem associated with the differential equation $-\frac{\partial^2 \psi}{\partial x^2}+x^2(i x)^\epsilon\psi=E\psi$. The method of solution is numerical in nature using Mathematica 9's built in NDSolve function with a 9th order adaptive Runge-Kutta method and a standardized shooting algorithm. All eigenvalues are quoted to 6 places and have been calculated to higher precision in order to ensure 6 valid places. This problem was oringally solved and published under: Real Spectra in Non-Hermitian Hamiltonians Having PT Symmetry by Carl M Bender and Stefan Boettcher [Phys.Rev.Lett. 80 (1998) 5243-5246]. This dataset demonstrates independent reproduction of the original results and makes the data underlying the figures in the paper available to those who wish to check their own results. Further eigenvalues and supporting information to follow in this dataset [DWH - 14/2/2013].

List of times of postings on PTsymmetry.net.

List of times of postings on PTsymmetry.net.

Poster by Tim Evans (Imperial College London), Karen Gurney of Evidence (a division of ThomsonReuters) and Daniel Hook of Symplectic Ltd, Imperial College and Washington University, St. Louis, USA. Presented by Daniel Hook at the INORMS conference entitled "Collaboration Profiling in UK Higher Education".

List of times of postings on PTsymmetry.net. Altered a little bit.