I wonder what a source of truth is -- not necessarily an SSOT for the customer/company data, which is what Salesforce could become.

very organized

Synergies for Europe's Research Infrastructures in the Social Sciences (SERISS)

one of the most beneficial services at AUB

This workshop is offered once per semester to faculty members and research assistants

Inside the very specific realm of personal knowledge bases, TiddlyWiki is the killer app when it comes to using blocks and having structured, translatable data behind them.

Data-Lake-Management-Plattformen

Kovacs, M., Hoekstra, R., & Aczel, B. (2021). The Role of Human Fallibility in Psychological Research: A Survey of Mistakes in Data Management. Advances in Methods and Practices in Psychological Science, 4(4), 25152459211045930. https://doi.org/10.1177/25152459211045930

<small><cite class='h-cite via'>ᔥ <span class='p-author h-card'>Wikipedia</span> in Index card - Wikipedia (<time class='dt-published'>07/03/2021 21:36:58</time>)</cite></small>

Armeni, Kristijan, Loek Brinkman, Rickard Carlsson, Anita Eerland, Rianne Fijten, Robin Fondberg, Vera Ellen Heininga, et al. ‘Towards Wide-Scale Adoption of Open Science Practices: The Role of Open Science Communities’. MetaArXiv, 6 October 2020. https://doi.org/10.31222/osf.io/7gct9.

Aczel, Balazs, Marton Kovacs, and Rink Hoekstra. ‘The Role of Human Fallibility in Psychological Research: A Survey of Mistakes in Data Management’. PsyArXiv, 5 November 2020. https://doi.org/10.31234/osf.io/xcykz.

ORWG Virtual Meeting 08/09/2020 https://www.youtube.com/playlist?list=PLOA0aRJ90NxvXtMt5Si5ukmR9LYfvDueB (n.d.)

Outbreak.info. (n.d.). Outbreak.Info. Retrieved October 25, 2020, from https://outbreak.info/

AI and control of Covid-19 coronavirus. (n.d.). Artificial Intelligence. Retrieved October 15, 2020, from https://www.coe.int/en/web/artificial-intelligence/ai-and-control-of-covid-19-coronavirus

2019nCOV. (n.d.). MOBS Lab. Retrieved October 2, 2020, from https://www.mobs-lab.org/2019ncov.html

Gollwitzer, M., Abele-Brehm, A., Fiebach, C., Ramthun, R., Scheel, A. M., Schönbrodt, F., & Steinberg, U. (2020). Data Management and Data Sharing in Psychological Science: Revision of the DGPs Recommendations. https://doi.org/10.31234/osf.io/24ncs

Spiegelhalter, D. (2020). Use of “normal” risk to improve understanding of dangers of covid-19. BMJ, 370. https://doi.org/10.1136/bmj.m3259

Building the New Economy · Works in Progress. (n.d.). Works in Progress. Retrieved June 16, 2020, from https://wip.mitpress.mit.edu/new-economy

Hong, H., Wang, N., & Yang, J. (2020). Implications of Stochastic Transmission Rates for Managing Pandemic Risks (Working Paper No. 27218; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27218

Reacting Quickly and Protecting Jobs: The Short-​Term Impacts of the COVID-19 Lockdown on the Greek Labor Market. COVID-19 and the Labor Market. (n.d.). IZA – Institute of Labor Economics. Retrieved July 27, 2020, from https://covid-19.iza.org/publications/dp13516/

La, V.-P., Pham, T.-H., Ho, T. M., Hoàng, N. M., Linh, N. P. K., Vuong, T.-T., Nguyen, H.-K. T., Tran, T., Van Quy, K., Ho, T. M., & Vuong, Q.-H. (2020). Policy response, social media and science journalism for the sustainability of the public health system amid the COVID-19 outbreak: The Vietnam lessons [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/cfw8x

ReconfigBehSci on Twitter: “brief video describing the https://t.co/zDXjvZFtkM initiative here: https://t.co/8rJEuDj7B4” / Twitter. (n.d.). Twitter. Retrieved July 5, 2020, from https://twitter.com/scibeh/status/1279123525916405762

ReconfigBehSci on Twitter: “SciBeh now has a video describing our initative! watch, retweet.... https://t.co/j3TF3zfdIt” / Twitter. (n.d.). Twitter. Retrieved June 29, 2020, from https://twitter.com/scibeh/status/1277260447029362688

Supporting Open Science Data Curation, Preservation, and Access by Libraries. (2020, June 25). https://www.youtube.com/watch?v=SbmGWHpzAHs&feature=youtu.be

DELVE group publishes evidence paper on the use of face masks in tackling Coronavirus (COVID-19) pandemic | Royal Society. (2020 May 04). https://royalsociety.org/news/2020/05/delve-group-publishes-evidence-paper-on-use-of-face-masks/

Lewandowsky, S. (2020, June 1). A tale of two island nations: Lessons for crisis knowledge management. Psychonomic Society Featured Content. https://featuredcontent.psychonomic.org/a-tale-of-two-island-nations-lessons-for-crisis-knowledge-management/

Peikert, A., & Brandmaier, A. M. (2019). A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker. https://doi.org/10.31234/osf.io/8xzqy

The Coerciveness of the Primary Key: Infrastructure Problems in Human Services Work

Would be great to connect these efforts with others who work on this from the data end, e.g. RDA as mentioned above.

Also, the presentation at http://www.gfbr.global/wp-content/uploads/2018/12/PG4-Alpha-Ahmadou-Diallo.pptx states

This data will be made available to the public and to scientific and humanitarian health communities to disseminate knowledge about the disease, support the expansion of research in West Africa, and improve patient care and future response to an outbreak.

but the notion of public access is not clearly articulated in the present article.

Does it have a name and online presence? The details provided here go beyond what's given in reference 13, but some more detail would still be useful, e.g. to connect the initiative to efforts directed at data management and curation more generally, for instance in the framework of the Research Data Alliance, https://www.rd-alliance.org/ .

Sounds like part of the problem Vitrine technologie-éducation has been tackling with Ceres, a Learning Object Repository with a Semantic core.

Have yet to notice much discussion of the relationships between SIS (Student Information Systems), CRM (Customer Relationship Management), ERP (Enterprise Resource Planning), and LMS (Learning Management Systems).

YES, ASK US. Also, we love to work with faculty on managing their data!

What is the sharing standard? What are the consequences of not sharing? What is the enforcement mechanism?

There are three primary sharing mechanisms I can think of today: email, usb stick, and dropbox (née ftp).

The dropbox option is supplanting ftp which comes from another era, but still satisfies an important niche for larger data sets and/or higher-volume or anonymous traffic.

Dropbox, email and usb are all easily accessible parts of the day-to-day consumer workflow; they are all trivial to set up without institutional support or, importantly, permission.

An email account is already provisioned by default for everyone or, if the institutional email offerings are not sufficient, a person may easily set up a 3rd-party email account with no permission or hassle.

Data management alternatives to these three options will have slow or no adoption until the barriers to access and use are as low as email; the cost of entry needs to be no more than *a web browser, an email address, and no special permission required".

Who cares most about the 20-year rule? This is an ideal that appeals to some, but in practice even the most zealous adherents can't picture what this looks like in some concrete way-- except in the most traditional ways: physical paper journals in libraries are tangible examples of the 20-year rule.

Until we have a digital equivalent for data I don't blame people looking for tenure or jobs for not caring about this ideal if we can't provide a clear picture of how to achieve this widely at an institutional level. For digital materials I think the picture people have in their minds is of tape backup. Maybe this is generational? New generations not exposed widely to cassette tapes, DVDs, and other physical media that "old people" remember, only then will it be possible to have a new ideal that people can see in their minds-eye.

I agree with the key component mentioned here, but I feel the term data entropy is an unhelpful crutch.

Data management practices:

• create
• organize
• manage
• describe
• preserve
• share

Categories of data management activities:

• storage
  • backup/archival data storage
  • identifying appropriate data repositories
  • day-to-day data storage
  • interacting with data repositories
• more information
  • obtaining more information about curation best practices
  • identifying appropriate data registries
  • search portals
• metadata
  • assigning permanent identifiers to data
  • creating/publishing descriptions of data
  • capturing computational provenance
• funding
  • identifying funding sources for curation support
• planning
  • creating data management plans at proposal time