AO: They write: “capacity is meant to last, but to do so it must be remembered, accumulated, repaired and protected.” This echoes recent work looking at the unaccounted for labor that often is not planned for or forgotten with regards to technology (in education for example). This is described in the context of digital infrastructures by Crooks and also Kenner in different examples.
AO: In her preface, she notes: I am “refusing to choose between categories. … I am both a Western and a West African scientists. … a bicontinental existence currently contributes more than a full-time scientific employment in Nigeria. … I know many other African scientists who have straddled two continents, making the most of the increased “networkedness” of science today. (x).
AO: Tichenor notes that data collection takes many forms. Diagnostic data are the skeleton upon which a representation of malaria in Senegal is estimated. The data that stand in for Senegal from the global malaria perspective are based on approximate diagnoses performed by nurses, physicians, and laboratory technicians and involves a process of “filling out” data that raises questions about data ownership, utility, and representativeness.
AO: Tichnor notes the multiple challenges with defining malaria, including the changing standards (between clinical reporting of Malaria to microscophy testing in 2008); experiences of different malarias; continued ambiguity in diagnostic method. These lead to very rough “approximations” that Tichenor argues is a key part of mapping global boundaries of malaria.
AO: “The data the Ministry demands from health workers do not represent, by design, the local realities.” (444)
“Professional membership organizations, networking initiatives, data sharing sites, and Web 2.0 tools offer scientists important means of communicating with peers, gaining access to data resources, and disseminating their own data outside of traditional publication routes” (41)
They note that “data engagement channels and access to information are severely curtailed due to micro-economic concerns.” (43)
Mavhunga notes the social network of people who were key nodes of information sharing (e.g. Javuendava pg 155 and MaTshangana’s network page 180). He also notes some people as being key in shielding the information and protecting it (dying instead of sharing the info page 197) while others sold out and shared the information (page 204). The “data” and “info” therefore are not technical in this case but human. This evokes Simone AbdouMalique's idea of "people as infrastructure", esp. in the context of information sharing.
“Most important genomic data is available from freely accessible databases and sophisticated analyses can be performed using free software.” (459)
Okeke notes that most Africans are relegated to collection work in partnerships related to global health and genomics work. “In the last half-century far too many African scientists are engaged in what they themselves view as “collecting” biological specimens, which are then dispatched to laboratories elsewhere on the globe. African scientists have viewed their conduit role in this “postal research” as derogatory (Ntoumi et al. 2004; Oyebade 2010; Crane 2013; Sawyerr 2004; Fullwiley 2011).6 For them, bioscience has matured, but Little Brother has not. Others spend a few weeks a year hosting “parachute scientists” who visit only to grab specimens and then disappear into the real world of scientific inquiry (Okwaro and Geissler 2015; Fullwiley 2011).
“Postal” and “parachute” research inevitably addresses remote or “global” questions, not local ones (Kebede and Polderman 2004; Costello and Zumla 2000; Okeke 2011; Wolffers, Adjei, and van der Drift 1998; Karim and Karim 2010; Fullwiley 2011). We know a lot because of this type of research, but very little of this knowledge has been applied to health care on the continent (Fullwiley 2011).”
This polemic critique of Gabrielle Hecht's archiving practices by Lance van Sittert asks how her approach is any different from the mine management that she critiques. He questions whether there really was no correspondence with the mine beforehand to establish the existence of an archive on site or if her assumption was that because this was Africa, no archive would exist. He notes that fifteen years after Hecht’s hasty scavenging, the Mounana mine archive is no more. He critiques her for not archiving or saving any of the materials for future researchers to use.
Tousignant looks at data on toxics and notes it has been growing (albeit slowly). The data on accidental and voluntary acute poisonings have been compiled from hospital or clinical records.
She notes that most international initiatives do not directly support the production of data on pathways, levels, and distributions of exposure but rather, generally address the already known sources of risk (E.g. promoting safer techniques of mercury use without investigating exposure).
Tousignant notes that the Sahelian ecotoxicology’s methodological and institutional infrastructures were entangled in justifications for prolonging the project and in the project practices for accumulating data and making it usable over time.
Tousignant notes: “Presumably only the best (or favorite) pharmacy students were given access to project machines and lab supplies for their thesis work; the majority had to make do with bibliographic essays, or compilations of clinical data and questionnaire results.” She includes in a footnote: “Only a small fraction of thesis research involved laboratory analysis, however. A few theses were bibliographic essays on specific toxic risks or analytical methods, while the majority involved “paper-based” research, that is, involving the collection and analysis of existing data (such as information in clinical registers) or of responses to questionnaires (for example, on knowledge and practices pertaining to toxic risks such as pesticide use among farmers).” The data they are working with appears to largely be quantitative data.
Tousignant notes that her interlocutors highlighted the need to generate their own data: “the CAP’s statistician explained to me that poison, as a cause of morbidity and mortality, was not (yet) a category in national health statistics. Poisoning might be recorded in clinical registers, but not always, and was not an accurate reflection of the causes and magnitude of the problem. It was important, then, for the center to generate its own data.
Excerpt from interlocutor: “We need to collect data on the causal link between poisoning and pesticides [...] we have to create an observatory, for long-term follow-up [...] when you ask for money, you don’t ask for the minimum. We already know there are problems with the use of pesticides [...] we need to get blood samples, we need to get a spectro[photometer] and reagents [...] we need field testing kits [...] we need a sociologist too [...] An epidemiological study for 2.5 million [CFA francs]?... We need 25 million! [...] We need data! [...] We will do everything. We will follow, in a month, in a year... [...] We need right away to put in study and analyses. We have to follow up on a long period.” (Chapter 5)
She does not explicitly discuss their data practices.