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GitHub - ICIJ/datashare: Investigative journalism 3.0.
DataShare aims at allowing for valuable knowledge about people and companies locked within hundreds of pages of documents inside a computer to be sieved into indexes and shared securely within a network of trusted individuals, fostering unforeseen collaboration and prompting new and better investigations that uncover corruption, transnational crime and abuse of power.
archives  tools  icij  collaboration  dj  databases 
2 days ago by paulbradshaw
Nine Eyes of Google Street View | Net Art Anthology
Nine Eyes of Google Street View is both an archival project and a conceptual meditation on the state of photography in a time of automated imagemaking on a massive scale.In 2008, Jon Rafman began to collect screenshots of images from Google Street View. At the time, Street View was a relatively ne...
photography  google  art  archives  2007  automation  car  image  joannemcneil  johnrafman 
3 days ago by atran
MAT
We imagine indigenous cultures as the epitome of caring and sharing. In scholarly and popular representations of Indigenous Australians, resources are freely shared within kin groups. Land is a cosmological actor and cannot be owned. Besides, survival in harsh environments requires complete cooperation. But traditionally in Indigenous Australian cultures, knowledge is anything but open (Keen 1994). Controlling the circulation of knowledge is the basis of traditional authority (perhaps all human societies are ‘knowledge economies’).

In postcolonial societies, the control of knowledge held by indigenous communities and produced from indigenous resources (including indigenous bodies and body parts) has become ‘political’ as well as ‘cultural’. Indigenous communities fight to maintain control over lands and peoples, and Western research is often in the firing line. Aware of the history of racial science and more recent scandals (Anderson 2002; Reardon 2005), indigenous people may be wary of participating in research (Smith 2012). Calls to global knowledge and the greater good that motivate ‘altruistic’ participation in the general community ring false to those who feel that scientific progress is made not for their benefit, but at their expense....

Everywhere we are struggling with when to share and when to withhold. Perhaps the critical point is not whether something is open or closed, but who has the control to make this decision. The world of open access proliferates the decisions that need to be made....

Yet when a journal is able to reach a readership no longer defined exclusively by members of a discipline (if this is ever the case), and anticipates that wider market of readers/consumers, does that not change the kinds of things (topics, concerns, methods) that are valued and thus supported by open-access journals and their editors, peer reviewers, etc.? Open access is not only about dissemination; it is about the expectation of an audience as a mode of scholarly production....

‘Opening’ work to collaboration with local actors (as described by Sharon above) does not necessary lead to greater equality. I think we should question the notions of the public sphere and of sharing that underlie normative understandings of open access. As any anthropologist who has read their Mauss can tell you, sharing can be a profoundly coercive practice as much as a leveling one. Sharing and collaboration restrain as much as they generate.
archives  data  open_access  openness  indigenous  anthropology 
5 days ago by shannon_mattern
reconstitute the world « Bethany Nowviskie
What kinds of indigenous knowledge do we neglect to represent—or fail to understand—in our digital libraries? What tacit and embodied understandings? What animal perspectives? What do we in fact choose, through those failures, to extinguish from history—and what does that mean at this precise cultural and technological moment? On the other hand, what sorts of records and recordable things should we let go—should we be working as hard as possible to protect from machine learning for the good of vulnerable communities and creatures—knowing, as we do, that technologies of collection and analysis are by nature tools of surveillance and structures of extractive power? And, finally—from an elegiac archive, a library of endings, can we foster new kinds of human—or at the very least, humane—agency? ...

The Biodiversity Heritage Library is a Smithsonian-based international consortium and digitization collective of botanical and natural history libraries.... “Mining Biodiversity” was the theme of a productive 2015 NEH Digging into Data grant, which coupled novel text-mining and visualization techniques with crowdsourcing and outreach. And projects like PaleoDeepDive and GeoDeepDive represent AI-assisted efforts to pull out so-called “dark data” from its bibliographic tar pits: those idiosyncratic features in scientific journal literature like tables and figures, that have not easily leant themselves to structured searching and the assembly of comparative datasets. ... Meanwhile projects like Digital Life, out of the University of Massachusetts, “aim to preserve the heritage of life on Earth through creating and sharing high-quality… 3D models of living organisms.” ... They do this through photogrammetry, circling living creatures with their awesomely-named BeastcamTM, and converting the resulting, overlapping 2d images to highly-accurate 3d representations. And thus the field of biodiversity informatics continues to grow and pose data curation challenges of various sorts, ranging from the preservation and analysis of 3d models to large-scale environmental data generated through remote sensing, to the collection and analysis of, for instance, audio data relating to deforestation of the Brazilian rainforest. ... The use of machine learning in monitoring contexts of various sorts is rapidly becoming the norm, and it is big business more often than community-led conservation. Microsoft has recently announced an “AI for Earth” initiative which commits $50 million dollars in grant funds over the next 5 years for “artificial intelligence projects that support clean water, agriculture, climate, and biodiversity”...

And because we no longer design these little agents to understand things—we simply filter them based on their ability to pass tests—we don’t really understand, ourselves, how they work. Mostly we just understand those tests. ...

a truly successful set of machine learning algorithms can begin to produce its own training data to advance in understanding and pass more real-world tests. This is the generation of completely imagined, fictional and truly speculative collections: manufactured botany, or book pages—leaves that never were. It’s information that the machine has dreamt up from its past encounters with real-world data...

Abelardo Gil-Fournier is applying this technology to his artistic work on predictive landscapes, presented a couple of weeks ago as a workshop in Linz, called Machine Learning: An Earthology of Moving Landforms. This is (I quote) “ongoing research on the image character and temporality of planetary surfaces.” As his collaborator Jussi Parikka puts it, “we can experiment with the correlation of an “imaged” past (the satellite time-lapses) with a machine generated “imaged” future and test how futures work; how do predicted images compare against historical datasets and time-lapses and present their own … temporal landscapes meant to run just a bit ahead of [their] time.”...

Here we have Nao Tokui’s “Imaginary Soundscapes,” a “web-based sound installation, where viewers can freely walk around Google Street View and immerse themselves in an artificial soundscape [that is based on the visual qualities of real-world spaces, but has been wholly] “imagined” by… deep learning models.”...

I’d love to see, for instance, an artistic or analytical machine learning experiment using BHL collections and Scottish flower painter Patrick Syme’s 1814 update to Werner’s Nomenclature of Colors. This book has been recently digitized and republished by the Smithsonian. It contains “the color names used by naturalists, zoologists and archaeologists through the 19th century,” and it shaped Charles Darwin’s formal chromatic vocabulary on the voyage of the Beagle. How might we use machine learning to identify references to these standardized colors in images and texts throughout Western library collections, and put them into conversation with indigenous color-names and perspectives on creatures living and lost?
libraries  archives  ecology  machine_vision  artificial_intelligence  erasure  privacy  security  climate_change  speculation  deep_fakes 
5 days ago by shannon_mattern
Recommendations for good Linked Open Data Good practices
Recommendations for Good Practices When Initiating Linked Open Data (LOD) in Museums and Other Cultural-Heritage Institutions These recommendations are excerpted from the AAC publication, Overview and Recommendations for Good Practices [PDF] The following text is meant for museums and other types o via Pocket
archives  data  howto  libraries  linkeddata  museums 
6 days ago by kintopp
How Long Can Our Content Last? • Robin Rendle
But the biggest flaw with all this digital preservation stuff isn’t HTML or CSS in my opinion. It’s the concept of a domain that we rent. Today we borrow spaces on the web and put up our flimsy little flags on top. And then the links get lost in a shuffle between apartments or jobs, between marriages or administrations. Or when someone accidentally unplugs something. Or, tragically, if someone dies.
web  archives  preservation 
8 days ago by madamim

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