The Data-Pooling Problem

Mattioli, Michael

doi:10.2139/ssrn.2671939

Cited by 9 publications

(7 citation statements)

References 5 publications

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“…Data is treated and exchanged as a market commodity with the aim of producing data-driven innovation, new services, and economic benefits for all the parties involved (Carballa Smichowski, 2019; Kawalek and Bayat, 2017). DSPs are described as horizontal joint initiatives among data holders to aggregate data from different sources to create more value through their combination (Mattioli, 2017; Shkabatur, 2019). Their overall rationality is attuned with dominant discursive regimes of Big Data (Kitchin, 2014) and lies in the assumption that ‘the greatest advantages of data sharing may be in the combination of data from multiple sources, compared or 'mashed up' in innovative ways’ (Mayer-Schonberger and Cukier, 2013 cited in Mattioli, 2017: 184).…”

Section: Data Sharing Poolsmentioning

confidence: 99%

“…There is reciprocity between partner organisations, but only data holders are involved, as data subjects tend to be excluded from the relation and are at best depicted as passively benefiting from it. Although use cases of DSPs do exist, examples in practice are still few (Mattioli, 2017). A practical limitation consists in the transaction costs, such as data preparation, ensuring privacy and interoperability challenges, which put small businesses and under-funded entities at a disadvantage (GovLab, 2018).…”

Section: Data Sharing Poolsmentioning

confidence: 99%

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Emerging models of data governance in the age of datafication

et al. 2020

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The article examines four models of data governance emerging in the current platform society. While major attention is currently given to the dominant model of corporate platforms collecting and economically exploiting massive amounts of personal data, other actors, such as small businesses, public bodies and civic society, take also part in data governance. The article sheds light on four models emerging from the practices of these actors: data sharing pools, data cooperatives, public data trusts and personal data sovereignty. We propose a social science-informed conceptualisation of data governance. Drawing from the notion of data infrastructure we identify the models as a function of the stakeholders’ roles, their interrelationships, articulations of value, and governance principles. Addressing the politics of data, we considered the actors’ competitive struggles for governing data. This conceptualisation brings to the forefront the power relations and multifaceted economic and social interactions within data governance models emerging in an environment mainly dominated by corporate actors. These models highlight that civic society and public bodies are key actors for democratising data governance and redistributing value produced through data. Through the discussion of the models, their underpinning principles and limitations, the article wishes to inform future investigations of socio-technical imaginaries for the governance of data, particularly now that the policy debate around data governance is very active in Europe.

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Section: Data Sharing Poolsmentioning

confidence: 99%

Section: Data Sharing Poolsmentioning

confidence: 99%

Emerging models of data governance in the age of datafication

et al. 2020

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“…Osrednjo vlogo ima podatkovni skrbnik, ki podatke zbere ter na podlagi opravljene analize posreduje vpoglede ponudnikom podatkov. Podatke lahko proda tudi naprej proti plačilu licence za uporabo podatkov, zato bazeni delujejo tudi kot licenčni modeli (Mattioli, 2017). Ob tem je podatkovni bazen namenjen predvsem združevanju različnih poslovnih deležnikov, kjer medsebojno sodelovanje le-teh pomaga pri identifikaciji in zapolnjevanju vrzeli v znanju, zmanjšajo se podvajanja podatkov, glavna prednost pa je omogočeno solastništvo podatkov, kar prispeva k centralizirani izmenjavi podatkov znotraj poslovnih ekosistemov.…”

Section: Koncept Podatkovno Vodene Organizacijeunclassified

Znanstveno-raziskovalni trendi na področju digitalne preobrazbe

Баггиа

2021

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Digitalna preobrazba organizacij predstavlja ključni element uspeha v sodobnem poslovnem svetu. Pri tem pomembno vlogo igrajo vodstvo in zaposleni v organizaciji, ter njihovo poznavanje konceptov in tehnologij digitalne preobrazbe. V monografiji predstavljamo aktualne teme s področja digitalne preobrazbe, ki bodo organizacijam z nizkim digitalnim indeksom in ostalim udeležencem v procesu digitalne preobrazbe v pomoč pri lažjem prehodu v digitalno poslovanje. Med prebojnimi tehnologijami, ki jih zasledimo na področju digitalne preobrazbe so v znanstveni monografiji predstavljeni primeri večkriterijskih ekspertnih sistemov za podporo odločanja, opredeljena je vloga podatkov v sodobni organizaciji, obravnavano je področje interneta stvari in kiberfizičnih sistemov, predstavljeni so pristopi k transformaciji modela poslovnega procesa v tehnologijo veriženja blokov, ter podane smernice za učinkovito oblavdovanje kibernetskih tveganj v času pandemije. Poleg primerov uporabe sodobnih tehnologij je predstavljena tudi zasnova prilagodljivega modela strateškega upravljanja informatike.

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“…47 SWD (2018) 125 final, p. 5. 48 Lundqvist (2018), p. 146; see for the economic background of data pooling, referring to the ''big data anticommons'', Mattioli (2017), pp. 189 et seq.…”

Section: Sharing Platform Parametersmentioning

confidence: 99%

“…55 See Plantin et al (2018), p. 7. 56 See https://www.healthcare-informatics.com/news-item/analytics/vivli-launches-clinical-researchdata-sharing-platform; see for cancer research data in particular, https://projectdatasphere.org/ projectdatasphere/html/home; see alsoMattioli (2017), pp. 205 et seq.…”

mentioning

confidence: 99%