A Formal Category Theoretical Framework for Multi-model Data Transformations

Valter Johan Edvard Uotila; Jiaheng Lu

doi:10.1007/978-3-030-93663-1_2

A Formal Category Theoretical Framework for Multi-model Data Transformations

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussa › Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

Abstrakti

Data integration and migration processes in polystores and multi-model database management systems highly benefit from data and schema transformations. Rigorous modeling of transformations is a complex problem. The data and schema transformation field is scattered with multiple different transformation frameworks, tools, and mappings. These are usually domain-specific and lack solid theoretical foundations. Our first goal is to define category theoretical foundations for relational, graph, and hierarchical data models and instances. Each data instance is represented as a category theoretical mapping called a functor. We formalize data and schema transformations as Kan lifts utilizing the functorial representation for the instances. A Kan lift is a category theoretical construction consisting of two mappings satisfying the certain universal property. In this work, the two mappings correspond to schema transformation and data transformation.

Alkuperäiskieli	englanti
Otsikko	Heterogeneous Data Management, Polystores, and Analytics for Healthcare : VLDB Workshops, Poly 2021 and DMAH 2021
Toimittajat	El Kindi Rezig, Vijay Gadepally, Timothy Mattson, Michael Stonebraker, Tim Kraska, Fusheng Wang, Gang Luo, Jun Kong, Alevtina Dubovitskaya
Kustantaja	Springer, Cham
Julkaisupäivä	20 elok. 2021
Sivut	14-28
ISBN (painettu)	978-3-030-93662-4
ISBN (elektroninen)	978-3-030-93663-1
DOI - pysyväislinkit	https://doi.org/10.1007/978-3-030-93663-1_2
Tila	Julkaistu - 20 elok. 2021
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisuussa
Tapahtuma	VLDB Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances - Kesto: 20 elok. 2021 → 20 elok. 2021

Tieteenalat

113 Tietojenkäsittely- ja informaatiotieteet

Pääsy asiakirjaan

10.1007/978-3-030-93663-1_2

Uotila_A Formal categoryLopullinen julkaistu versio, 432 KBLisenssi: Muu

https://arxiv.org/abs/2201.04905Lisenssi: CC BY-NC-ND

1 Kutsuesitelmä

Multi-model Query Processing Meets Category Theory and Functional Programming
Valter Johan Edvard Uotila (Puhuja), Jiaheng Lu (Puhuja), Dieter Gawlick (Puhuja), Zhen Hua Liu (Puhuja), Souripriya Das (Puhuja) & Gregory Pogossiants (Puhuja)
20 elok. 2021
Aktiviteetti: Puhe- tai esitystyypit › Kutsuesitelmä

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Uotila, V. J. E., & Lu, J. (2021). A Formal Category Theoretical Framework for Multi-model Data Transformations. teoksessa E. K. Rezig, V. Gadepally, T. Mattson, M. Stonebraker, T. Kraska, F. Wang, G. Luo, J. Kong, & A. Dubovitskaya (Toimittajat), Heterogeneous Data Management, Polystores, and Analytics for Healthcare: VLDB Workshops, Poly 2021 and DMAH 2021 (Sivut 14-28). Springer, Cham. https://doi.org/10.1007/978-3-030-93663-1_2

Uotila, Valter Johan Edvard ; Lu, Jiaheng. / A Formal Category Theoretical Framework for Multi-model Data Transformations. Heterogeneous Data Management, Polystores, and Analytics for Healthcare: VLDB Workshops, Poly 2021 and DMAH 2021. Toimittaja / El Kindi Rezig ; Vijay Gadepally ; Timothy Mattson ; Michael Stonebraker ; Tim Kraska ; Fusheng Wang ; Gang Luo ; Jun Kong ; Alevtina Dubovitskaya. Springer, Cham, 2021. Sivut 14-28

@inproceedings{3744874ad9b14a42a4a272f51e2381b0,

title = "A Formal Category Theoretical Framework for Multi-model Data Transformations",

abstract = "Data integration and migration processes in polystores and multi-model database management systems highly benefit from data and schema transformations. Rigorous modeling of transformations is a complex problem. The data and schema transformation field is scattered with multiple different transformation frameworks, tools, and mappings. These are usually domain-specific and lack solid theoretical foundations. Our first goal is to define category theoretical foundations for relational, graph, and hierarchical data models and instances. Each data instance is represented as a category theoretical mapping called a functor. We formalize data and schema transformations as Kan lifts utilizing the functorial representation for the instances. A Kan lift is a category theoretical construction consisting of two mappings satisfying the certain universal property. In this work, the two mappings correspond to schema transformation and data transformation.",

keywords = "113 Computer and information sciences, multi-model databases, data transformations, category theory",

author = "Uotila, {Valter Johan Edvard} and Jiaheng Lu",

year = "2021",

month = aug,

day = "20",

doi = "10.1007/978-3-030-93663-1_2",

language = "English",

isbn = "978-3-030-93662-4",

pages = "14--28",

editor = "Rezig, {El Kindi} and Vijay Gadepally and Timothy Mattson and Michael Stonebraker and Tim Kraska and Fusheng Wang and Gang Luo and Jun Kong and Alevtina Dubovitskaya",

booktitle = "Heterogeneous Data Management, Polystores, and Analytics for Healthcare",

publisher = "Springer, Cham",

address = "Switzerland",

note = "VLDB Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances ; Conference date: 20-08-2021 Through 20-08-2021",

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Uotila, VJE & Lu, J 2021, A Formal Category Theoretical Framework for Multi-model Data Transformations. julkaisussa EK Rezig, V Gadepally, T Mattson, M Stonebraker, T Kraska, F Wang, G Luo, J Kong & A Dubovitskaya (toim), Heterogeneous Data Management, Polystores, and Analytics for Healthcare: VLDB Workshops, Poly 2021 and DMAH 2021. Springer, Cham, Sivut 14-28, VLDB Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances, 20/08/2021. https://doi.org/10.1007/978-3-030-93663-1_2

A Formal Category Theoretical Framework for Multi-model Data Transformations. / Uotila, Valter Johan Edvard ; Lu, Jiaheng.
Heterogeneous Data Management, Polystores, and Analytics for Healthcare: VLDB Workshops, Poly 2021 and DMAH 2021. toim. / El Kindi Rezig; Vijay Gadepally; Timothy Mattson; Michael Stonebraker; Tim Kraska; Fusheng Wang; Gang Luo; Jun Kong; Alevtina Dubovitskaya. Springer, Cham, 2021. s. 14-28.

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussa › Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

TY - GEN

T1 - A Formal Category Theoretical Framework for Multi-model Data Transformations

AU - Uotila, Valter Johan Edvard

AU - Lu, Jiaheng

PY - 2021/8/20

Y1 - 2021/8/20

N2 - Data integration and migration processes in polystores and multi-model database management systems highly benefit from data and schema transformations. Rigorous modeling of transformations is a complex problem. The data and schema transformation field is scattered with multiple different transformation frameworks, tools, and mappings. These are usually domain-specific and lack solid theoretical foundations. Our first goal is to define category theoretical foundations for relational, graph, and hierarchical data models and instances. Each data instance is represented as a category theoretical mapping called a functor. We formalize data and schema transformations as Kan lifts utilizing the functorial representation for the instances. A Kan lift is a category theoretical construction consisting of two mappings satisfying the certain universal property. In this work, the two mappings correspond to schema transformation and data transformation.

AB - Data integration and migration processes in polystores and multi-model database management systems highly benefit from data and schema transformations. Rigorous modeling of transformations is a complex problem. The data and schema transformation field is scattered with multiple different transformation frameworks, tools, and mappings. These are usually domain-specific and lack solid theoretical foundations. Our first goal is to define category theoretical foundations for relational, graph, and hierarchical data models and instances. Each data instance is represented as a category theoretical mapping called a functor. We formalize data and schema transformations as Kan lifts utilizing the functorial representation for the instances. A Kan lift is a category theoretical construction consisting of two mappings satisfying the certain universal property. In this work, the two mappings correspond to schema transformation and data transformation.

KW - 113 Computer and information sciences

KW - multi-model databases

KW - data transformations

KW - category theory

U2 - 10.1007/978-3-030-93663-1_2

DO - 10.1007/978-3-030-93663-1_2

M3 - Conference contribution

SN - 978-3-030-93662-4

SP - 14

EP - 28

BT - Heterogeneous Data Management, Polystores, and Analytics for Healthcare

A2 - Rezig, El Kindi

A2 - Gadepally, Vijay

A2 - Mattson, Timothy

A2 - Stonebraker, Michael

A2 - Kraska, Tim

A2 - Wang, Fusheng

A2 - Luo, Gang

A2 - Kong, Jun

A2 - Dubovitskaya, Alevtina

PB - Springer, Cham

T2 - VLDB Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances

Y2 - 20 August 2021 through 20 August 2021

ER -

Uotila VJE , Lu J. A Formal Category Theoretical Framework for Multi-model Data Transformations. julkaisussa Rezig EK, Gadepally V, Mattson T, Stonebraker M, Kraska T, Wang F, Luo G, Kong J, Dubovitskaya A, toimittajat, Heterogeneous Data Management, Polystores, and Analytics for Healthcare: VLDB Workshops, Poly 2021 and DMAH 2021. Springer, Cham. 2021. s. 14-28 doi: 10.1007/978-3-030-93663-1_2

A Formal Category Theoretical Framework for Multi-model Data Transformations

Abstrakti

Tieteenalat

Pääsy asiakirjaan

Aktiviteetit

Multi-model Query Processing Meets Category Theory and Functional Programming

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