Data Mashups Questions
From Horizon Project
[edit] 2008 Research Agenda Topics
[edit] 2007 Activity |
[edit] The 2008 Horizon Report: Toward a Research Agenda
With the release of the 2008 edition in this annual series, the NMC is continuing the concerted, international effort started last year to describe a research agenda based on the six practices and technologies featured in the 2008 edition of the Horizon Report. You are invited to participate in this process, contribute to the discussion, and help shape directions for future research in these topics across higher education.
[edit] What are the missing pieces for Data Mashups to be implemented in higher education?
- People are not aware of how and where to begin for these tools. Understanding of how to use the tools or how find and use the data is a problem.
- Database integration, documentation for lay users, extensive tagging across databases.
- Privacy issues inherent in types of data
- Better access to data and better standards for creating and publishing that data.
- Depends upon objectives- definition
- A clear definition and understanding of the process.
- Metadata standards
- Data directories
- Simple to use tools for creating mashups from heterogeneous data sets (commonly found types, like spreadsheet and SQL databases.)
- This is so new teachers haven't heard of it yet- so had to get "buyin"
- Promotion and discussion of it; studies on the impact of learning
- Standards to get varied systems to work together. Or...like Google Earth, the vendor develops them. The issue is Google Earth is not open source. You are at the will of Google.
- Best practices or examples of how it can be used
- Getting the concepts across
- Data modules for tools to describe events and listen to them so they can be captured and used- no mashups interface.
- Clear definition of what a mashup might be.
- Concerns on privacy- guidance and policies, what is intellectual property?
- Concerns about privacy; What about intellectual property for data?
- Open standards for data from different sources can be integrated.
- Policies and guidelines for legal use; best practices (e.g. privacy rights)
- Are resources licensed by universities to be available only on property
- Time
- Permissions for using data
- Add your comments here
[edit] What kind of research would you like to see around Data Mashups
- Are the mashups helping people to understand a concept or a problem?
- Case studies of applications
- Validation of data sources
- Establishing best practices (maybe "beta practices")
- Research about developing more/better tools for people to easily create data mashups
- Provide examples beyond google maps- other educational applications
- Metadata standards, API standards for sharing info
- What visualization formats are most common. Are there organizational frames beyond maps that have brand appeal?
- Studies of impact of learning to foster buy-in because start-up will be energy intensive
- Simpler, lower tech (in appearance) tools teachers are willing to try
- "Guinea pig" experimentation- widely scattered eclectic group of people to implement and use
- How do students feel about the knowledge/data created through mashups?
- Quantitative research on practices
- Modeling the tool
- What tools should talk to one another?
- What value emerges- just because you can, should you?
- Do mashups augment understanding of the information?
- Gather data and propose "best practices"
- Qualitative studies. Look into a group of people to start the conversation.
- Intelligent data mashup and processing to enable various data to be used
- Do existing laws offer the appropriate and sufficient rules or do we need new regulations?
- What are the implications of doing mashups with digital resources available in virtual worlds; legal issues associated with mashups created in virtual worlds.
- Add your comments here
[edit] What are the learning implications of Data Mashups?
- Visualization of data to clarify problems.
- Quantitive literacies.
- Pushing students to think about information and data as dynamic and able to be manipulated.
- Don't know yet, but should find out.
- Dynamic knowledge; selective content; challenge: verifiability
- Gives students freedom to create visualizations of data.
- Teaching student literacy with data visualization design.
- If students are contributing data and their contribution is an "outline", are they creative or just "wrong"?
- New sources of information - same data but presented in novel way.
- Data visualization seems to be good. What kind of learning styles does lend itself too?
- 3-D thinking, more sources, more creativity. Also, of possibly less creativity, plagarism.
- Social networking, also intellectual property studies. Media studies.
- Simple interface for extract and display data.
- Faculty need to introduce students to best practices and legal requirements.
- Add your comments here
