author Fritz Breithaupt. “Sometimes we commit atrocities not out of a failure of empathy but rather as a direct consequence of successful, even overly successful, empathy,” he writes in his forthcoming book The Dark Sides of Empathy.
Breithaupt, who directs the Experimental Humanities Lab at Indiana University, argues that empathy is a morally ambiguous capacity, one that can lead us astray if we don’t understand its many sides.
People assume that empathy is good because it is good for the recipient of empathy — I’m actually skeptical about this.
How is empathy good for the empathizer?
“vampiristic empathy.”
Vampiristic empathy is a form of empathy where people want to manipulate the people they empathize with so that they can, through them, experience the world in such a way that they really enjoy it.
An extreme case of this is helicopter parenting. Helicopter parents are constantly trying to steer their kids in the directions they think are the right directions. Of course they want the best for their children.
In a sense, extreme helicopter parents are robbing their kids of a selfhood so that they can basically project their own self into these kids.
empathy can actually make us more polarized instead of bringing us together.
Humans are very quick to take sides. And when you take one side, you take the perspective of that side. You can see the painful parts of that perspective and empathize with them, and that empathy can fuel seeing the other side as darker and darker or more dubious.
Are there other downsides to empathy?
[Empathizers] may overextend themselves. If you are a medical doctor who sees a lot of suffering and pain every day, it can very quickly become too much. Something like a third of medical doctors suffer from “empathy burnout” that is so severe that it affects their functioning as doctors and their personal life. They become the victim of feeling empathy. My note: and some therapists can suffer of “hollow” empathy – an empathy not as a human feeling but as a tool to extend their ability/control in the room.
Also, “MInnesota Nice” can acquire a rather different meaning seen through the lens of this research
My core argument here is that in many cases of altruistic help or humanitarian aid, people actually don’t really empathize as much with the person in need. They identify more with the helper, the hero, the person who intervenes even if it’s an imaginary helper.
If you want recognition and if that doesn’t come, it can turn into resentment.
we can learn to use empathy in a somewhat controlled way. We can learn when to block it, when to not allow empathy to be manipulated and when to fully turn it on.
Yes, we are born with empathy, but it needs constant practice [to know] when to use it and when not to use it. So the dark sides are so important to know because they teach us that in some cases you shouldn’t empathize.
https://sched.co/JAqk
the type of data: wikipedia. the dangers of learning from wikipedia. how individuals can organize mitigate some of these dangers. wikidata, algorithms.
IBM Watson is using wikipedia by algorythms making sense, AI system
youtube videos debunked of conspiracy theories by using wikipedia.
semantic relatedness, Word2Vec
how does algorithms work: large body of unstructured text. picks specific words
lots of AI learns about the world from wikipedia. the neutral point of view policy. WIkipedia asks editors present as proportionally as possible. Wikipedia biases: 1. gender bias (only 20-30 % are women).
conceptnet. debias along different demographic dimensions.
citations analysis gives also an idea about biases. localness of sources cited in spatial articles. structural biases.
geolocation on Twitter by County. predicting the people living in urban areas. FB wants to push more local news.
danger (biases) #3. wikipedia search results vs wkipedia knowledge panel.
collective action against tech: Reddit, boycott for FB and Instagram.
data labor: what the primary resources this companies have. posts, images, reviews etc.
boycott, data strike (data not being available for algorithms in the future). GDPR in EU – all historical data is like the CA Consumer Privacy Act. One can do data strike without data boycott. general vs homogeneous (group with shared identity) boycott.
the wikipedia SPAM policy is obstructing new editors and that hit communities such as women.
how to access at different levels. methods and methodological concerns. ethical concerns, legal concerns,
tweetdeck for advanced Twitter searches. quoting, likes is relevant, but not enough, sometimes screenshot
engagement option
social listening platforms: crimson hexagon, parsely, sysomos – not yet academic platforms, tools to setup queries and visualization, but difficult to algorythm, the data samples etc. open sources tools (Urbana, Social Media microscope: SMILE (social media intelligence and learning environment) to collect data from twitter, reddit and within the platform they can query Twitter. create trend analysis, sentiment analysis, Voxgov (subscription service: analyzing political social media)
graduate level and faculty research: accessing SM large scale data web scraping & APIs Twitter APIs. Jason script, Python etc. Gnip Firehose API ($) ; Web SCraper Chrome plugin (easy tool, Pyhon and R created); Twint (Twitter scraper)
Facepager (open source) if not Python or R coder. structure and download the data sets.
TAGS archiving google sheets, uses twitter API. anything older 7 days not avaialble, so harvest every week.
social feed manager (GWUniversity) – Justin Litman with Stanford. Install on server but allows much more.
legal concerns: copyright (public info, but not beyond copyrighted). fair use argument is strong, but cannot publish the data. can analyize under fair use. contracts supercede copyright (terms of service/use) licensed data through library.
methods: sampling concerns tufekci, 2014 questions for sm. SM data is a good set for SM, but other fields? not according to her. hashtag studies: self selection bias. twitter as a model organism: over-represnted data in academic studies.
methodological concerns: scope of access – lack of historical data. mechanics of platform and contenxt: retweets are not necessarily endorsements.
ethical concerns. public info – IRB no informed consent. the right to be forgotten. anonymized data is often still traceable.
table discussion: digital humanities, journalism interested, but too narrow. tools are still difficult to find an operate. context of the visuals. how to spread around variety of majors and classes. controversial events more likely to be deleted.
takedowns, lies and corrosion: what is a librarian to do: trolls, takedown,
development kit circulation. familiarity with the Oculus Rift resulted in lesser reservation. Downturn also.
An experience station. clean up free apps.
question: spherical video, video 360.
safety issues: policies? instructional perspective: curating,WI people: user testing. touch controllers more intuitive then xbox controller. Retail Oculus Rift
app Scatchfab. 3modelviewer. obj or sdl file. Medium, Tiltbrush.
College of Liberal Arts at the U has their VR, 3D print set up.
Penn State (Paul, librarian, kiniseology, anatomy programs), Information Science and Technology. immersive experiences lab for video 360.
CALIPHA part of it is xrlibraries. libraries equal education. content provider LifeLiqe STEM library of AR and VR objects. https://www.lifeliqe.com/
libraians, IT staff, IDs. help faculty with course design, primarily online, master courses. Concordia is GROWING, mostly because of online students.
solve issues (putting down fires, such as “gradebook” on BB). Librarians : research and resources experts. Librarians helping with LMS. Broadening definition of Library as support hub.
“Formulating a product, you better know about ethics and understand legal frameworks.”
These days a growing number of people are concerned with bringing more talk of ethics into technology. One question is whether that will bring change to data-science curricula.
Following major data breaches and privacy scandals at tech companies like Facebook, universities including Stanford, the University of Texas and Harvard have all added ethics courses into computer science degree programs to address tech’s “ethical dark side,” the New York Times has reported.
As more college and universities consider incorporating humanities courses into technical degree programs, some are asking what kind of ethics should be taught.
at a session on the umbrella concept of “mixed reality” (abbreviated XR) here Thursday, attendees had some questions for the panel’s VR/AR/XR evangelists: Can these tools help students learn? Can institutions with limited budgets pull off ambitious projects? Can skeptical faculty members be convinced to experiment with unfamiliar technology?
Yale has landed on a “hub model” for project development — instructors propose projects and partner with students with technological capabilities to tap into a centralized pool of equipment and funding. (My note: this is what I suggest in my Chapter 2 of Arnheim, Eliot & Rose (2012) Lib Guides)
Several panelists said they had already been getting started on mixed reality initiatives prior to the infusion of support from Educause and HP, which helped them settle on a direction
While 3-D printing might seem to lend itself more naturally to the hard sciences, Yale’s humanities departments have cottoned to the technology as a portal to answering tough philosophical questions.
institutions would be better served forgoing an early investment in hardware and instead gravitating toward free online products like Unity, Organon and You by Sharecare, all of which allow users to create 3-D experiences from their desktop computers.
XR technologies encompassing 3D simulations, modeling, and production.
This project sought to identify
current innovative uses of these 3D technologies,
how these uses are currently impacting teaching and learning, and
what this information can tell us about possible future uses for these technologies in higher education.
p. 5 Extended reality (XR) technologies, which encompass virtual reality (VR) and augmented reality (AR), are already having a dramatic impact on pedagogy in higher education. XR is a general term that covers a wide range of technologies along a continuum, with the real world at one end and fully immersive simulations at the other.
p. 6The Campus of the Future project was an exploratory evaluation of 3D technologies for instruction and research in higher education: VR, AR, 3D scanning, and 3D printing. The project sought to identify interesting and novel uses of 3D technology
p. 7 HP would provide the hardware, and EDUCAUSE would provide the methodological expertise to conduct an evaluation research project investigating the potential uses of 3D technologies in higher education learning and research.
The institutions that participated in the Campus of the Future project were selected because they were already on the cutting edge of integrating 3D technology into pedagogy. These institutions were therefore not representative, nor were they intended to be representative, of the state of higher education in the United States. These institutions were selected precisely because they already had a set of use cases for 3D technology available for study
p. 9 At some institutions, the group participating in the project was an academic unit (e.g., the Newhouse School of Communications at Syracuse University; the Graduate School of Education at Harvard University). At these institutions, the 3D technology provided by HP was deployed for use more or less exclusively by students and faculty affiliated with the particular academic unit.
p. 10 definitions
there is not universal agreement on the definitions of these
terms or on the scope of these technologies. Also, all of these technologies
currently exist in an active marketplace and, as in many rapidly changing markets, there is a tendency for companies to invent neologisms around 3D technology.
A 3D scanner is not a single device but rather a combination of hardware and
software. There are generally two pieces of hardware: a laser scanner and a digital
camera. The laser scanner bounces laser beams off the surface of an object to
determine its shape and contours.
p. 11 definitions
Virtual reality means that the wearer is completely immersed in a computer
simulation. Several types of VR headsets are currently available, but all involve
a lightweight helmet with a display in front of the eyes (see figure 2). In some
cases, this display may simply be a smartphone (e.g., Google Cardboard); in other
cases, two displays—one for each eye—are integrated into the headset (e.g., HTC
Vive). Most commercially available VR rigs also include handheld controllers
that enable the user to interact with the simulation by moving the controllers
in space and clicking on finger triggers or buttons.
p. 12 definitions
Augmented reality provides an “overlay” of some type over the real world through
the use of a headset or even a smartphone.
In an active technology marketplace, there is a tendency for new terms to be
invented rapidly and for existing terms to be used loosely. This is currently
happening in the VR and AR market space. The HP VR rig and the HTC Vive
unit are marketed as being immersive, meaning that the user is fully immersed in
a simulation—virtual reality. Many currently available AR headsets, however, are
marketed not as AR but rather as MR (mixed reality). These MR headsets have a
display in front of the eyes as well as a pair of front-mounted cameras; they are
therefore capable of supporting both VR and AR functionality.
p. 13 Implementation
Technical difficulties.
Technical issues can generally be divided into two broad categories: hardware
problems and software problems. There is, of course, a common third category:
human error.
p. 15 the technology learning curve
The well-known diffusion of innovations theoretical framework articulates five
adopter categories: innovators, early adopters, early majority, late majority, and
laggards. Everett M. Rogers, Diffusion of Innovations, 5th ed. (New York: Simon and Schuster, 2003).
It is also likely that staff in the campus IT unit or center for teaching and learning already know who (at least some of) these individuals are, since such faculty members are likely to already have had contact with these campus units.
Students may of course also be innovators and early adopters, and in fact
several participating institutions found that some of the most creative uses of 3D technology arose from student projects
p. 30 Zeynep Tufekci, in her book Twitter and Tear Gas
definition: There is no necessary distinction between AR and VR; indeed, much research
on the subject is based on a conception of a “virtuality continuum” from entirely
real to entirely virtual, where AR lies somewhere between those ends of the
spectrum. Paul Milgram and Fumio Kishino, “A Taxonomy of Mixed Reality Visual Displays,” IEICE Transactions on Information Systems, vol. E77-D, no. 12 (1994); Steve Mann, “Through the Glass, Lightly,” IEEE Technology and Society Magazine 31, no. 3 (2012): 10–14.
For the future of 3D technology in higher education to be realized, that
technology must become as much a part of higher education as any technology:
the learning management system (LMS), the projector, the classroom. New
technologies and practices generally enter institutions of higher education as
initiatives. Several active learning classroom initiatives are currently under
way,36 for example, as well as a multi-institution open educational resources
(OER) degree initiative.37
p. 32 Storytelling
Some scholars have argued that all human communication
is based on storytelling;41 certainly advertisers have long recognized that
storytelling makes for effective persuasion,42 and a growing body of research
shows that narrative is effective for teaching even topics that are not generally
thought of as having a natural story, for example, in the sciences.43
p. 33 accessibility
The experience of Gallaudet University highlights one of the most important
areas for development in 3D technology: accessibility for users with disabilities.
p. 34 instructional design
For that to be the case, 3D technologies must be incorporated into the
instructional design process for building and redesigning courses. And for that
to be the case, it is necessary for faculty and instructional designers to be familiar
with the capabilities of 3D technologies. And for that to be the case, it may not be necessary but would certainly be helpful for instructional designers to collaborate closely with the staff in campus IT units who support and maintain this hardware.
Every institution of higher education has a slightly different organizational structure, of course, but these two campus units are often siloed. This siloing may lead to considerable friction in conducting the most basic organizational tasks, such as setting up meetings and apportioning responsibilities for shared tasks. Nevertheless, IT units and centers for teaching and learning are almost compelled to collaborate in order to support faculty who want to integrate 3D technology into their teaching. It is necessary to bring the instructional design expertise of a center for teaching and learning to bear on integrating 3D technology into an instructor’s teaching (My note: and where does this place SCSU?) Therefore, one of the most critical areas in which IT units and centers for teaching and learning can collaborate is in assisting instructors to develop this integration and to develop learning objects that use 3D technology. p. 35 For 3D technology to really gain traction in higher education, it will need to be easier for instructors to deploy without such a large support team.
p. 35 Sites such as Thingiverse, Sketchfab, and Google Poly are libraries of freely
available, user-created 3D models.
ClassVR is a tool that enables the simultaneous delivery of a simulation to
multiple headsets, though the simulation itself may still be single-user.
p. 37 data management:
An institutional repository is a collection of an institution’s intellectual output, often consisting of preprint journal articles and conference papers and the data sets behind them.49 An institutional repository is often maintained by either the library or a partnership between the library and the campus IT unit. An institutional repository therefore has the advantage of the long-term curatorial approach of librarianship combined with the systematic backup management of the IT unit. (My note: leaves me wonder where does this put SCSU)
Sharing data sets is critical for collaboration and increasingly the default for
scholarship. Data is as much a product of scholarship as publications, and there
is a growing sentiment among scholars that it should therefore be made public.50
Our survey polled 232 faculty members across the country about their use of technology in the classroom, their likes and dislikes, their predictions for the future and more. The majority of respondents (68 percent) come from public institutions, with 28 percent from private nonprofits and 4 percent working at for-profit schools. Seventy-two percent work at four-year colleges or universities; 26 percent are at community colleges (the remaining 2 percent designated their institutional level as “other”).
Respondents represent institutions of a range of sizes, with about one-third (32 percent) working in colleges or universities with 2,500 to 9,999 students. Just under half (45 percent) of respondents are from institutions with 10,000 students or more.
Our respondents are veterans of higher education: The largest group (47 percent) has more than 20 years of experience, with 81 percent logging at least 11 years in the field.
The top three most common school and college types among our respondents are education (22 percent), business/business administration (17 percent) and liberal arts (12 percent). But overall, respondents work in a wide range of disciplines, from engineering and medicine to humanities and fine arts. The top 10 states with the most survey respondents are New York, Texas, California, Florida, Georgia, Virginia, Illinois, Missouri, Pennsylvania and Massachusetts.
the popular hip-hop lyrics Web siteRap Genius, will announce a pilot project to use hip-hop to teach science in 10 New York City public schools. The pilot is small, but its architects’ goals are not modest. Dr. Emdin, who has written a book called “Urban Science Education for the Hip-Hop Generation,”
hip-hop “cypher,” participants stand in a circle and take turns rapping, often supporting or playing off one another’s rhymes.
“All of those things that are happening in the hip-hop cypher are what should happen in an ideal classroom.”
++++++++++++++++++++
Students analyze rap lyrics with code in digital humanities class
Some teachers are finding a place for coding in English, music, science, math and social studies, too
by TARA GARCÍA MATHEWSON October 18, 2018
Fifteen states now require all high schools to offer computer science courses. Twenty-three states have created K-12 computer science standards. And 40 states plus the District of Columbia allow students to count computer science courses toward high school math or science graduation requirements. That’s up from 12 states in 2013, when Code.org launched, aiming to expand access to computer science in U.S. schools and increase participation among girls and underrepresented minorities in particular.
United States digital literacy frameworks tend to focus on educational policy details and personal empowerment, the latter encouraging learners to become more effective students, better creators, smarter information consumers, and more influential members of their community.
National policies are vitally important in European digital literacy work, unsurprising for a continent well populated with nation-states and struggling to redefine itself, while still trying to grow economies in the wake of the 2008 financial crisis and subsequent financial pressures
African digital literacy is more business-oriented.
Middle Eastern nations offer yet another variation, with a strong focus on media literacy. As with other regions, this can be a response to countries with strong state influence or control over local media. It can also represent a drive to produce more locally-sourced content, as opposed to consuming material from abroad, which may elicit criticism of neocolonialism or religious challenges.
p. 14 Digital literacy for Humanities: What does it mean to be digitally literate in history, literature, or philosophy? Creativity in these disciplines often involves textuality, given the large role writing plays in them, as, for example, in the Folger Shakespeare Library’s instructor’s guide. In the digital realm, this can include web-based writing through social media, along with the creation of multimedia projects through posters, presentations, and video. Information literacy remains a key part of digital literacy in the humanities. The digital humanities movement has not seen much connection with digital literacy, unfortunately, but their alignment seems likely, given the turn toward using digital technologies to explore humanities questions. That development could then foster a spread of other technologies and approaches to the rest of the humanities, including mapping, data visualization, text mining, web-based digital archives, and “distant reading” (working with very large bodies of texts). The digital humanities’ emphasis on making projects may also increase
Digital Literacy for Business: Digital literacy in this world is focused on manipulation of data, from spreadsheets to more advanced modeling software, leading up to degrees in management information systems. Management classes unsurprisingly focus on how to organize people working on and with digital tools.
Digital Literacy for Computer Science: Naturally, coding appears as a central competency within this discipline. Other aspects of the digital world feature prominently, including hardware and network architecture. Some courses housed within the computer science discipline offer a deeper examination of the impact of computing on society and politics, along with how to use digital tools. Media production plays a minor role here, beyond publications (posters, videos), as many institutions assign multimedia to other departments. Looking forward to a future when automation has become both more widespread and powerful, developing artificial intelligence projects will potentially play a role in computer science literacy.
In traditional instruction, students’ first contact with new ideas happens in class, usually through direct instruction from the professor; after exposure to the basics, students are turned out of the classroom to tackle the most difficult tasks in learning — those that involve application, analysis, synthesis, and creativity — in their individual spaces. Flipped learning reverses this, by moving first contact with new concepts to the individual space and using the newly-expanded time in class for students to pursue difficult, higher-level tasks together, with the instructor as a guide.
Let’s take a look at some of the myths about flipped learning and try to find the facts.
Myth: Flipped learning is predicated on recording videos for students to watch before class.
Fact: Flipped learning does not require video. Although many real-life implementations of flipped learning use video, there’s nothing that says video must be used. In fact, one of the earliest instances of flipped learning — Eric Mazur’s peer instruction concept, used in Harvard physics classes — uses no video but rather an online text outfitted with social annotation software. And one of the most successful public instances of flipped learning, an edX course on numerical methods designed by Lorena Barba of George Washington University, uses precisely one video. Video is simply not necessary for flipped learning, and many alternatives to video can lead to effective flipped learning environments [http://rtalbert.org/flipped-learning-without-video/].
Fact: Flipped learning optimizes face-to-face teaching. Flipped learning may (but does not always) replace lectures in class, but this is not to say that it replaces teaching. Teaching and “telling” are not the same thing.
Myth: Flipped learning has no evidence to back up its effectiveness.
Fact: Flipped learning research is growing at an exponential pace and has been since at least 2014. That research — 131 peer-reviewed articles in the first half of 2017 alone — includes results from primary, secondary, and postsecondary education in nearly every discipline, most showing significant improvements in student learning, motivation, and critical thinking skills.
Myth: Flipped learning is a fad.
Fact: Flipped learning has been with us in the form defined here for nearly 20 years.
Myth: People have been doing flipped learning for centuries.
Fact: Flipped learning is not just a rebranding of old techniques. The basic concept of students doing individually active work to encounter new ideas that are then built upon in class is almost as old as the university itself. So flipped learning is, in a real sense, a modern means of returning higher education to its roots. Even so, flipped learning is different from these time-honored techniques.
Myth: Students and professors prefer lecture over flipped learning.
Fact: Students and professors embrace flipped learning once they understand the benefits. It’s true that professors often enjoy their lectures, and students often enjoy being lectured to. But the question is not who “enjoys” what, but rather what helps students learn the best.They know what the research says about the effectiveness of active learning
Assertion: Flipped learning provides a platform for implementing active learning in a way that works powerfully for students.
The Exposure Approach: we don’t provide a way for participants to determine if they learned anything new or now have the confidence or competence to apply what they learned.
The Exemplar Approach: from ‘show and tell’ for adults to show, tell, do and learn.
The Tutorial Approach: Getting a group that can meet at the same time and place can be challenging. That is why many faculty report a preference for self-paced professional development.build in simple self-assessment checks. We can add prompts that invite people to engage in some sort of follow up activity with a colleague. We can also add an elective option for faculty in a tutorial to actually create or do something with what they learned and then submit it for direct or narrative feedback.
The Course Approach: a non-credit format, these have the benefits of a more structured and lengthy learning experience, even if they are just three to five-week short courses that meet online or in-person once every week or two.involve badges, portfolios, peer assessment, self-assessment, or one-on-one feedback from a facilitator
The Academy Approach: like the course approach, is one that tends to be a deeper and more extended experience. People might gather in a cohort over a year or longer.Assessment through coaching and mentoring, the use of portfolios, peer feedback and much more can be easily incorporated to add a rich assessment element to such longer-term professional development programs.
The Mentoring Approach: The mentors often don’t set specific learning goals with the mentee. Instead, it is often a set of structured meetings, but also someone to whom mentees can turn with questions and tips along the way.
The Coaching Approach: A mentor tends to be a broader type of relationship with a person.A coaching relationship tends to be more focused upon specific goals, tasks or outcomes.
The Peer Approach:This can be done on a 1:1 basis or in small groups, where those who are teaching the same courses are able to compare notes on curricula and teaching models. They might give each other feedback on how to teach certain concepts, how to write syllabi, how to handle certain teaching and learning challenges, and much more. Faculty might sit in on each other’s courses, observe, and give feedback afterward.
The Self-Directed Approach:a self-assessment strategy such as setting goals and creating simple checklists and rubrics to monitor our progress. Or, we invite feedback from colleagues, often in a narrative and/or informal format. We might also create a portfolio of our work, or engage in some sort of learning journal that documents our thoughts, experiments, experiences, and learning along the way.
In 2014, administrators at Central Piedmont Community College (CPCC) in Charlotte, North Carolina, began talks with members of the North Carolina State Board of Community Colleges and North Carolina Community College System (NCCCS) leadership about starting a CBE program.
Building on an existing project at CPCC for identifying the elements of a digital learning environment (DLE), which was itself influenced by the EDUCAUSE publication The Next Generation Digital Learning Environment: A Report on Research,1 the committee reached consensus on a DLE concept and a shared lexicon: the “Digital Learning Environment Operational Definitions,
When: Friday, September 28, 8:30am-3:00pm Where: Wilson Research Collaboration Studio, Wilson Library Cost: Free; advanced registration is required
1968 was one of the most turbulent years of the 20th century. 2018 marks the 50th anniversary of that year’s landmark political, social and cultural events–events that continue to influence our world today.
Focusing on the importance of this 50 year anniversary we are calling out to all faculty, staff, students, and community partners to participate the workshop ‘Mapping 1968, Conflict and Change’. This all-day event is designed to bring people together into working groups based on common themes. Bring your talent and curiosity to apply an interdisciplinary approach to further explore the spatial context of these historic and/or current events. Learn new skills on mapping techniques that can be applied to any time in history. To compliment the expertise that you bring to the workshop, working groups will also have the support of library, mapping, and data science experts to help gather, create, and organize the spatial components of a given topic.
Workshop sponsors: Institute for Advanced Studies (IAS), U-Spatial, Liberal Arts Technologies & Innovation Services (LATIS), Digital Arts, Science & Humanities (DASH), and UMN Libraries.
Henneping County scanned the deeds, OCR, Python script to search. Data in an open source. covenant data. Local historian found microfishes, the language from the initial data. e.g. eugenics flavor: arian, truncate.
storymaps.arcgis.com/en/gallery https://storymaps.arcgis.com/en/gallery/#s=0 cloud-based mapping software. ArcGIS Online. organizational account for the U, 600 users. over 700 storymaps creates within the U, some of them are not active, share all kind of data: archive data on spreadsheet, but also a whole set of data within the software; so add the data or use the ArcGIS data and use templates. web maps into the storymap app, Living Atlas: curated set of data: hunderd sets of data, from sat images, to different contents. 846 layers of data, imagery, besides org account, one can create maps within the free account with limited access. data browser to use my own data – Data Enrichment to characterized my data. census data from 2018 and before,
make plan, create a storyboard, writing for the web, short and precise (not as writing for a journal), cartographic style, copyright, citing the materials, choosing the right map scale for each page. online learning materials, some only thru org account ESRI academy has course catalogue. Mapping 101, Dekstop GIS 101, Collector 101, Imagery 101, SQL 101, Story Maps 101,
The “Mapping 1968, Conflict and Change” planning committee is very pleased with the amount of interest and the wonderful attendance at Friday’s gathering. Thank you for attending and actively participating in this interdisciplinary workshop!
To re-cap and learn more on your thoughts and expectations of the workshop we would be grateful if you can take a few moments to complete the workshop evaluation. Please complete the evaluation even if you were unable to attend last Friday, there are questions regarding continued communication and the possibility for future events of this kind.
The Research Grants Programme is intended for early career scholars of all nationalities and in any field of the Humanities. They must have a particular interest in cultural heritage and take a digital humanities approach. Applicants must hold a PhD, with no more than 7 years of experience after the completion of their PhD. With duly justified exceptions, their projects must be hosted by institutions, i.e. a university, a research centre, a library lab or a museum, working in one of the European Union member states.
