Fieldwork Project Application<\/a><\/h3>\n<\/div>\n<\/div>\n<\/div>\nProject Timelines<\/h2>\n
| Stage<\/th>\n | Summer Projects<\/th>\n | Fall Projects<\/th>\n | Spring Projects<\/th>\n | Description<\/th>\n<\/tr>\n<\/thead>\n |
|---|---|---|---|---|
| Application Deadline<\/td>\n | March 1<\/td>\n | April 1<\/td>\n | Sept 1<\/td>\n | Once we have your application we\u2019ll begin working with you to understand your project needs.<\/td>\n<\/tr>\n |
| Feasibility Analysis and Decision<\/td>\n | Mar 15<\/td>\n | Jun 1<\/td>\n | Nov 1<\/td>\n | Program Director and Sponsor agree on a general project plan, with specifics to be further elaborated during the Planning Phase. Administrative Fee is due for all accepted projects.<\/td>\n<\/tr>\n |
| Planning Phase Begins<\/td>\n | Mar 15<\/td>\n | Jun 15<\/td>\n | Nov 15<\/td>\n | The project is scheduled to be offered in the next semester, a faculty mentor is designated, and detailed planning on project scope begins. Students are selected to work on the project.<\/td>\n<\/tr>\n |
| Project Implementation Begins<\/td>\n | May<\/td>\n | Sept<\/td>\n | Jan<\/td>\n | Students meet regularly with their faculty mentor and your organization, providing frequent updates on their progress.<\/td>\n<\/tr>\n |
| Project Presentations<\/td>\n | Dec<\/td>\n | Dec<\/td>\n | May<\/td>\n | At the end of each semester, our students present their Fieldwork results at our Data Science Fair.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\nMulti-Semester Projects<\/h2>\nStudents must register for Fieldwork on a semester to semester basis, but can take the Fieldwork course more than once. We encourage long term projects, where multiple teams of students may work on different phases of the same project for multiple semesters or academic years.<\/p>\n We will work to maximize continuity between semesters, preferentially placing students on the same project (if desired) and assigning the same faculty mentors. There is no application necessary for continued projects. Projects spanning multiple semesters do require payment of half of the administrative fee, which covers the cost of faculty mentors.<\/p>\n Faculty Team Members<\/h3>\nFieldwork project scope may exceed the capabilities of a single student, or a team of students. This may be due to the volume of work necessary, or because the work requires specific expertise beyond the capabilities of an MSDS student. Sponsors may (and encouraged to) include their own personnel in a project to augment the team\u2019s capacity or expertise.<\/p>\n Sponsors who do not have internal resources to fulfill the additional project needs may also engage RCNJ faculty with required expertise. We will work with you to identify the right faculty member(s) for your project – from within the Data Science faculty or from other faculty groups across the College.<\/p>\n Faculty Team Member fees are determined by a tiered pricing model based on necessary time commitment, estimated during the planning phase of the project.<\/p>\n Computing and Data Infrastructure<\/h3>\nIf a project requires specialized computing resources \/ data storage that a project sponsor does not wish to provide, RCNJ computing infrastructure may be used. In most cases, the MSDS program will utilize Amazon Web Services (AWS) to fulfill these infrastructure needs, however we can work with you to identify the most appropriate resources for your project. RCNJ will bill sponsors on a monthly basis for services used during the project.<\/p>\n Nondisclosure Agreements<\/h3>\nFieldwork projects often expose students to proprietary company information. Ramapo College, along with the students and faculty often sign separate non-disclosure agreements (NDA). Even with an executed NDA, company executives may permit students to speak in general terms about their assignment and, in some cases, list the research on their resumes. Regardless of whether an NDA is required, students are expected to treat the assignment as a private matter and conduct themselves in a professional manner at all times.<\/p>\n |
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