This week, I attended InCommon’s BaseCAMP. It’s a virtual event, like most events in recent memory. Virtual events have come a long way and the InCommon folks take advantage of Zoom and Remo to make their goal of “Learn. Share. Belong.” a reality. This was the most interactive online conference I’ve attended so far.
Here are some observations about why that was, in no particular order.
- Zoom was set to Meeting mode. Attendees could turn on their cameras and microphones when they wanted to.
- Presentations were live and speakers loved questions. Attendees asked questions in zoom chat. Either the speaker paused and asked if there were questions, or a monitor read questions at a natural pause.
- BaseCAMP ran Monday-Friday, 11-5 Central. The last optional hour and a half was on Remo (more about that below). BaseCAMP left time in the morning to do regular work.
- Sessions were 50 minutes. Between every session, there was a 10 minute break. The break was just enough time to get a drink and have a bio break, but not long enough to get started on other work that got interrupted once the next session started.
- During the breaks, they screen shared a duck race so people knew when to return. It also gave people something fun to watch and comment on. I don’t know what software they used, but costumed ducks swam as a timer counted down and one won at the end.
- Remo preserved the “hallway conversation” aspect of face-to-face conferences about as well as possible.
Remo is another conference product that is based on multiple rooms. Attendees see all of the rooms and who is in each room. BaseCAMP configured Remo to look like a series of campfires. Each campfire was numbered. When an attendee joined a campfire, they could speak with everyone there. This was a better format than zoom because zoom doesn’t show who is is what breakout room.
See post for more details: https://osrhe.peopleadmin.com/postings/452
Provide customer service/technical support for OneNet’s statewide Internet services.
Responsibilities and Duties
• Develops new system and application implementation plans, custom scripts and testing procedures to ensure operational reliability for the network group.
• Maintains process workflows for Netgroup ticket activities and implements new technologies, as applicable.
• Assist in network analysis and design for all network infrastructure.
• Ensures high availability and acceptable levels of performance of mission critical host computer resources.
• Actively support router/switch installations, modifications and upgrades.
• Support services such as packet filtering, firewall services, VPNs and router upgrades.
• Tier 2-3 support for the OneNet helpdesk for network-related issues.
• Assist lead engineer for MPLS network deployments.
Univ of Missouri
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UNL Institute of Agriculture and Natural Resources (IANR) and Agricultural Research Division Seeks Data Management Specialist
See website for more information: https://employment.unl.edu/
Description of Work :
This position will support our recent excellent faculty hires who are working on cutting edge research in their disciplines, and collaborating across disciplinary boundaries in our systems teams. The incumbent will work with the Holland Computing Center, ITS, Libraries, and external Federal partners (e.g., Agricultural Research Service, USDA) to initiate the development of agricultural data architecture, configuration, and analytic technologies that will allow our researchers to store (short and long-term), visualize, show workflow, use version control (i.e., keep previous versions), integrate heterogeneous data, capture metadata (that can be expandable), guarantee compatibility between systems, and offer onsite analysis (i.e., avoid downloads).
Recognizing that diversity within a context of inclusivity enhances creativity, innovation, impact, and a sense of belonging, the Institute of Agriculture and Natural Resources (IANR) and Agricultural Research Division are committed to creating learning, research, extension programming, and work environments that are inclusive of human diversity. We actively encourage applications from and nominations of individuals from underrepresented groups.
As an EO/AA employer, qualified applicants are considered for employment without regard to race, color, ethnicity, national origin, sex, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation. See http://www.unl.edu/equity/
Minimum Required Qualifications:
PhD in computer science, geospatial science, machine learning, agricultural sciences or related field; experience in data infrastructure design and development; experience in working with large-scale unstructured datasets: time series, geospatial (vector and raster), images, and video streams.
Understanding of agricultural and natural resources data; demonstrated ability to multitask; oral and written communication skills; student/staff training ability at the college level; experience in publishing technical papers, reports and other products (such as software packages and apps).
For questions or accommodations related to this position contact:
Job Posting: https://employment.unl.edu/