{ "cells": [ { "cell_type": "markdown", "id": "0", "metadata": {}, "source": [ "# EgoMaps" ] }, { "cell_type": "markdown", "id": "1", "metadata": {}, "source": [ "Every researcher is the center of his/her own universe. With EgoMaps, everyone can visualize that universe!\n", "\n", "Concretely, your EgoMap is a co-publication graph containing:\n", "\n", "- The *star*, i.e. you, the center of the universe\n", "- The *planets*, i.e. your co-authors\n", "- The *moons*, e.g. the co-authors of your co-authors\n", "\n", "By default, EgoMaps comprise up to 50 researchers, selecting first planets (sorted by number of collaborations), then moons (sorted by connectivity)." ] }, { "cell_type": "markdown", "id": "2", "metadata": {}, "source": [ ":::important\n", "\n", "**EgoMaps provide an engaging visualization of a researcher's egosystem.** In essence, they offer an intuitive way to explore and identify the research community or communities surrounding a given individual. By highlighting connections and relationships within a research network, EgoMaps aim to facilitate a deeper understanding of collaborative and thematic clusters in a researcher’s environment.\n", "\n", "It is important to emphasize that **EgoMaps are not designed nor intended to support any form of quantitative evaluation or ranking of researchers' work or impact.** Any such interpretation or usage is strongly discouraged, as the feature's primary purpose is to assist with qualitative exploration and visualization of research communities, not research assessment.\n", ":::" ] }, { "cell_type": "markdown", "id": "3", "metadata": {}, "source": [ ":::note\n", "\n", "For small tests, we query both HAL and DBLP (default behavior), but for large retrievals we use HAL only, as it is faster.\n", ":::" ] }, { "cell_type": "markdown", "id": "4", "metadata": {}, "source": [ "## Simple case" ] }, { "cell_type": "markdown", "id": "5", "metadata": {}, "source": [ "For basic scenarios, you just need to enter the name of the researcher. For example:" ] }, { "cell_type": "code", "execution_count": null, "id": "6", "metadata": {}, "outputs": [], "source": [ "from gismap.lab import EgoMap as Map\n", "\n", "celine = Map(\"Céline Comte\", dbs=\"hal\")\n", "celine.build()" ] }, { "cell_type": "markdown", "id": "7", "metadata": {}, "source": [ "You can display your EgoMap with `show_html` and save it with `save_html`" ] }, { "cell_type": "code", "execution_count": null, "id": "8", "metadata": {}, "outputs": [], "source": [ "celine.show_html()" ] }, { "cell_type": "markdown", "id": "9", "metadata": {}, "source": [ "## Adjusting the size" ] }, { "cell_type": "markdown", "id": "10", "metadata": {}, "source": [ "Depending on your degree, you may want to adjust the size of your universe with `target`. You can also personalize the *star* with a picture." ] }, { "cell_type": "code", "execution_count": null, "id": "11", "metadata": {}, "outputs": [], "source": [ "nidhi = Map(\n", " \"Nidhi Hegde (img: https://sites.ualberta.ca/~nidhih/images/circle1.png)\", dbs=\"hal\"\n", ")\n", "nidhi.build(target=60)" ] }, { "cell_type": "code", "execution_count": null, "id": "12", "metadata": {}, "outputs": [], "source": [ "nidhi.show_html()" ] }, { "cell_type": "markdown", "id": "13", "metadata": {}, "source": [ "## Not a researcher based in France and working in Computer Science?" ] }, { "cell_type": "markdown", "id": "14", "metadata": {}, "source": [ "You can specify the DB(s) you want to use.\n", "\n", "- If you work in Computer Science but are not based in France, you should use DBLP;\n", "- If you are a researcher based in France, HAL should work (example below);\n", "- If you are not based in France and not working on Computer Science, you should find a developper that can add your DB to Gismap!" ] }, { "cell_type": "code", "execution_count": null, "id": "15", "metadata": {}, "outputs": [], "source": [ "julie = Map(\n", " \"Julie Pagis (img: https://iris.ehess.fr/docannexe/file/3472/pagis_julie_photo_patrice_normand_2024.jpg)\",\n", " dbs=\"hal\",\n", ")\n", "julie.build()" ] }, { "cell_type": "code", "execution_count": null, "id": "16", "metadata": {}, "outputs": [], "source": [ "julie.show_html()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.8" } }, "nbformat": 4, "nbformat_minor": 5 }