{"id":4244,"date":"2018-05-08T13:51:16","date_gmt":"2018-05-08T19:51:16","guid":{"rendered":"http:\/\/ripl.lrs.org\/data-pathways\/?page_id=4244"},"modified":"2018-12-06T21:28:34","modified_gmt":"2018-12-07T04:28:34","slug":"data-competencies","status":"publish","type":"page","link":"https:\/\/www.ripleffect.org\/data-pathways\/data-competencies\/","title":{"rendered":"Data Competencies"},"content":{"rendered":"<h2 class=\"gdlr-heading-shortcode \"  style=\"color: #000000;font-size: 40px;\" ><\/span><span style=\"color: #000000\"><a style=\"color: #000000\" href=\"https:\/\/www.ripleffect.org\/data-pathways\/data-analysis\/\" target=\"_blank\" rel=\"noopener\">DATA ANALYSIS <\/a><\/span><\/h2>\n<div class=\"stunning-text-caption gdlr-skin-content\">\n<p>The competency, \u201cknowledge of and practices with data analysis\u201d involves the process of applying statistical and graphical techniques to data in order to discover useful information. Without data analysis skills, library staff can draw only very limited conclusions about patron data, reference statistics, and other library data. In general, data analysis requires:<\/p>\n<ul>\n<li>Apply statistical skills to data sets<\/li>\n<li>Use data analysis software<\/li>\n<li>Read and create charts and graphs<\/li>\n<\/ul>\n<p>For most library staff, the ability to use spreadsheet software, such as Excel or Google Sheets, will be sufficient, but some specialized positions may require the use of statistical software or data-related programming.<\/p>\n<a class=\"gdlr-button medium\" href=\"https:\/\/www.ripleffect.org\/data-pathways\/data-analysis\/\" target=\"_self\"  style=\"color:#ffffff; background-color:#cc0000; \"  >Go to Data Analysis<\/a>\n<div class=\"gdlr-shortcode-wrapper\"><div class=\"clear\"><\/div><div class=\"gdlr-item gdlr-divider-item\"  ><div class=\"gdlr-divider solid\"  style=\"width: 50%;\" ><\/div><\/div><\/div>\n<\/div>\n<h2 class=\"gdlr-heading-shortcode \"  style=\"color: #000000;font-size: 40px;\" ><\/span><a href=\"https:\/\/www.ripleffect.org\/data-pathways\/data-collection-planning-and-resource-management\/\" target=\"_blank\" rel=\"noopener\"><span style=\"color: #000000\">DATA PLANNING  &amp; RESOURCE MANAGEMENT<\/span><\/a><\/h2>\n<div class=\"stunning-text-caption gdlr-skin-content\">\n<p>The competency, &#8220;knowledge of and practices with data collection planning and resource management&#8221; involves the following:<\/p>\n<ul>\n<li>Defining the problem that needs to be solved<\/li>\n<li>Identifying data sources, and creating a data collection plan and setting goals<\/li>\n<li>Developing a plan for curating and managing collected data<\/li>\n<\/ul>\n<p>The purpose of this competency area is to familiarize library professionals on what the current best-practices for data collection planning and resource management are so that professionals have a better understanding of how to implement these skills within their workplace.<\/p>\n<a class=\"gdlr-button medium\" href=\"https:\/\/www.ripleffect.org\/data-pathways\/data-collection-planning-and-resource-management\/\" target=\"_self\"  style=\"color:#ffffff; background-color:#cc0000; \"  >Go to Data Planning &amp; Resource Management <\/a>\n<\/div>\n<div class=\"gdlr-shortcode-wrapper\"><div class=\"clear\"><\/div><div class=\"gdlr-item gdlr-divider-item\"  ><div class=\"gdlr-divider solid\"  style=\"width: 50%;\" ><\/div><\/div><\/div>\n<h2 class=\"gdlr-heading-shortcode \"  style=\"color: #000000;font-size: 40px;\" ><\/span><a href=\"https:\/\/www.ripleffect.org\/data-pathways\/communicating-data-and-using-different-types-of-data\/\" target=\"_blank\" rel=\"noopener\"><span style=\"color: #000000\">DATA STORYTELLING &amp; ADVOCACY<\/span><\/a><\/h2>\n<div class=\"stunning-text-caption gdlr-skin-content\">\n<p>The competency, &#8220;communicating data and using different types of data for advocacy and storytelling&#8221; involves the following:<\/p>\n<ul>\n<li>Define your goal &amp; audience<\/li>\n<li>Choose the right data &amp; find hidden insights<\/li>\n<li>Select effective visualizations to communicate a compelling story<\/li>\n<\/ul>\n<p>Using visual data analysis, professionals extract insights to find a narrative thread. By tailoring to the right audience, professionals can select the most effective format\/visualization to communicate a compelling story.<\/p>\n<a class=\"gdlr-button medium\" href=\"https:\/\/www.ripleffect.org\/data-pathways\/communicating-data-and-using-different-types-of-data\/\" target=\"_self\"  style=\"color:#ffffff; background-color:#cc0000; \"  >Go to Data Storytelling &amp; Advocacy<\/a>\n<div class=\"gdlr-shortcode-wrapper\"><div class=\"clear\"><\/div><div class=\"gdlr-item gdlr-divider-item\"  ><div class=\"gdlr-divider solid\"  style=\"width: 50%;\" ><\/div><\/div><\/div>\n<h2 class=\"gdlr-heading-shortcode \"  style=\"color: #000000;font-size: 40px;\" ><\/span><a href=\"https:\/\/www.ripleffect.org\/data-pathways\/practices-of-communicating-data\/\" target=\"_blank\" rel=\"noopener\"><span style=\"color: #000000\"> COMMUNICATING DATA TO INFORM DECISIONS<\/span><\/a><\/h2>\n<div class=\"stunning-text-caption gdlr-skin-content\">\n<p>The competency, &#8220;communicating data to inform decision-making&#8221; involves the following:<\/p>\n<ul>\n<li>Analyzing survey data<\/li>\n<li>Using collected data to revise and\/or create library programming<\/li>\n<li>Ability to frame an array of data points to set a baseline or present context.<\/li>\n<\/ul>\n<a class=\"gdlr-button medium\" href=\"https:\/\/www.ripleffect.org\/data-pathways\/practices-of-communicating-data\/\" target=\"_self\"  style=\"color:#ffffff; background-color:#cc0000; \"  >Go to Communicating Data to Inform Decisions<\/a>\n<\/div>\n<div class=\"gdlr-shortcode-wrapper\"><div class=\"clear\"><\/div><div class=\"gdlr-item gdlr-divider-item\"  ><div class=\"gdlr-divider solid\"  style=\"width: 50%;\" ><\/div><\/div><\/div>\n<h2 class=\"gdlr-heading-shortcode \"  style=\"color: #000000;font-size: 40px;\" ><\/span><a href=\"https:\/\/www.ripleffect.org\/data-pathways\/research-and-evaluation-methods\/\" target=\"_blank\" rel=\"noopener\"><span style=\"color: #000000\">RESEARCH &amp; EVALUATION METHODS<\/span><\/a><\/h2>\n<div class=\"stunning-text-caption gdlr-skin-content\">\n<p>The competency, &#8220;knowledge of and practices with public library research and evaluation methods&#8221; involves the following:<\/p>\n<ul>\n<li>Research design (case study, observation study, historical, longitudinal study, etc.)<\/li>\n<li>Instrument and protocol design (observations, surveys, interviews, &amp; focus groups)<\/li>\n<li>Plan for data documentation and management<\/li>\n<\/ul>\n<p>This competency is intended to help public library staff understand and effectively utilize the various forms of research and evaluation methods used in public libraries. To become familiar with this step will allow public library staff to move into the next phase of data analysis.<\/p>\n<a class=\"gdlr-button medium\" href=\"https:\/\/www.ripleffect.org\/data-pathways\/research-and-evaluation-methods\/\" target=\"_self\"  style=\"color:#ffffff; background-color:#cc0000; \"  >Go To Research &amp; Evaluation Methods<\/a>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>The competency, \u201cknowledge of and practices with data analysis\u201d involves the process of applying statistical and graphical techniques to data in order to discover useful information. Without data analysis skills, library staff can draw only very limited conclusions about patron data, reference statistics, and other library data. In general, data analysis requires: Apply statistical skills&#8230; <\/p>\n<div class=\"clear\"><\/div>\n<p><a href=\"https:\/\/www.ripleffect.org\/data-pathways\/data-competencies\/\" class=\"gdlr-info-font excerpt-read-more\">Read More<\/a><\/p>\n","protected":false},"author":7,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-4244","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.ripleffect.org\/data-pathways\/wp-json\/wp\/v2\/pages\/4244","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ripleffect.org\/data-pathways\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.ripleffect.org\/data-pathways\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.ripleffect.org\/data-pathways\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ripleffect.org\/data-pathways\/wp-json\/wp\/v2\/comments?post=4244"}],"version-history":[{"count":10,"href":"https:\/\/www.ripleffect.org\/data-pathways\/wp-json\/wp\/v2\/pages\/4244\/revisions"}],"predecessor-version":[{"id":4957,"href":"https:\/\/www.ripleffect.org\/data-pathways\/wp-json\/wp\/v2\/pages\/4244\/revisions\/4957"}],"wp:attachment":[{"href":"https:\/\/www.ripleffect.org\/data-pathways\/wp-json\/wp\/v2\/media?parent=4244"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}