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Hantering av forskningsdata: Datahanteringsprocessen på Hanken

För forskare och doktorander - datahanteringsprocess

(1) Innan datainsamling (under forskningsplaneringsfasen)

Steg 1. Överväg öppen publicering och öppna publiceringsalternativ.

Steg 2. Fyll i en beskrivning för databehandling.

Steg 3. Anhåll om etikprövning av Hankens forskningsetiska kommitté om din studie är en av de sex typerna som beskrivs i Etikprövning. Fyll i e-blanketten för anhållan om etikprövning.

Steg 4. Skriv en datahanteringsplan (DMP) och uppdatera den kontinuerligt,  se  DMP-guider och checklistor.

(2) Insamling av data (under aktiv forskningsfas)

Steg 5. Be om samtycke från forskningsdeltagarna om du samlar in personuppgifter eller om personuppgifterna tas från en annan källa än från forskningsdeltagarna. Se Samla in personuppgifter i avsnittet Datainsamling.

Steg 6. Förvara och säkerhetskopiera data säkert under forskningens gång, se  Datalagring och säkerhetskopiering.

  • Använd datalagringstjänster som tillhandahålls och underhålls av Hanken.
(3) Efter datainsamling (dela forskningsresultat)

Steg 7. Skriv en forskningsartikel och publicera den som  open access

Steg 8. Registrera din forskning i Haris, se Haris - Hankens forskningsdatabas i LibGuides.

Steg 9. Öppna och publicera dina data, se Att dela och arkivera data.

  • Se re3data.org för att hitta ett lämpligt arkiv. Rekommenderade förvaringsplatser är AilaIDA, Zenodo, Dryad, and Figshare.
  • Data med personlig information kan endast publiceras anonymiserade. Läs mera om hur du anonymiserar data i Anonymisation and Personal Data (Finlands samhällsvetenskapliga dataarkiv FSD).
  • Om dina data har ett långsiktigt värde, överväg att arkivera dina data i Fairdata-PAS av UKM.

Mer detaljerad beskrivning av datahanteringsprocessen finns i följande avsnitt Beskrivning av datahanteringsprocess.

För kandidat-, magister-, eMBA-studerande - datahanteringsprocess

Steg 1. Fyll i en beskrivning för datahantering.

  • Alla Hankens studerande ska fylla i e-blanketten Registrering av datahantering för studerande.
  • Det är viktigt att du identifierar dina datatyper eftersom olika datatyper kan ha olika krav på datahantering. Definitioner av olika datatyper anges i blanketten.
  • Följ instruktionerna i blanketten ifall du hanterar känslig eller konfidentiell data eller data som kräver etikprövning.

Steg 2. Informera dina forskningsdeltagare/informanter/respondenter om datainsamling.

  • Följ instruktionerna i  e-blanketten Registrering av datahantering för studerande.
  • Använd anteckningarna i blanketten för att informera dina forskningsdeltagare om datahantering, t.ex. hur du hanterar direkta identifierare eller när du raderar dina data.
  • Om du planerar att spara och lagra dina data för senare och delad användning i annan forskning än denna avhandling/kursuppgift (t.ex. för en vetenskaplig publikation), ska du informera dina forskningsdeltagare om detta.

Steg 3. Lagra och säkerhetskopiera data säkert under forskningens gång i datalagringstjänster som tillhandahålls och upprätthålls av Hanken (se Datalagring och säkerhetskopiering).

Steg 4: Radera data senast 12 månader efter att din avhandling lämnats in.

  • Om du planerar att spara, lagra, återanvända eller dela dina data för andra forskningsändamål än denna avhandling/kursuppgift (t.ex. för en vetenskaplig publikation) ska du diskutera detta med din handledare.

Forskningsdatats livscykel

Forskningsdatats livscykel (av DTU AIS Bibliometrics and Data Management - licensierat enligt CC0 1.0).

Beskrivning av datahanteringsprocess

(1) BEFORE DATA COLLECTION (RESEARCH PLANNING)

Stage 1. Consider open access publication outlets

  • Must-do for whom?
    • Principal Investigator PI of the research team
    • Researchers of the research team
    • Doctoral students
    • (Usually not BSc/MSc/eMBA students)
  • Must-do when?
    • Always/100% of studies.
  • Key decisions
    • Whether to prioritize an open access journal (see Gold OA in LibGuides on open access), or a journal with relatively inexpensive article processing charge (APC, see Discounts on APCs in LibGuides on open access) or a journal that allows for non-embargoed parallel publishing (see Green OA (self-archiving) in LibGuides on open access) over an equal quality non-open-access journal?
    • Whether to archive the data (or parts of it), once compiled, to a long-term data depository for the use of other researchers?
  • Key actions
    • Check the Open Access Policies from the journal publisher’s website.
    • Check also whether the journal offers a possibility (or requires) you to submit the research data (or sample of it) in case of publishing your research.
    • Contact the library haris@hanken.fi in order to learn about potential current contracts with the publisher about APCs or discounts.
  • Key implications to other stages
    • In Stage 7: Reconsider and recheck the open access journals checked at stage 1.
    • In Stage 2 and 4: Indicate in data processing description and data management plan in case you plan to target a journal that allows/requires submitting the dataset, or in case you plan to archive and share the data in a long-term depository
    • In Stage 10: Archive and share the data in a long-term depository, in case you plan to do so.

Stage 2. Fill in data processing description

  • Must-do for whom?
    • Principal Investigator PI of the research team
    • Researchers of the research team
    • Doctoral students
    • BSc/MSc/eMBA students
  • Must-do when?
    • Always/100% of studies.
  • Key decisions
    • Whether to gather data of your own, or utilize secondary data gathered by someone else/some organization
    • Whether to include (a) personal data about individuals (e.g., consumers, customers, or investors), (b) data gathered from individuals (e.g., company managers), or (c) no person-related data at all
      • If including (a) or (b): whether to gather/include direct identifier information (e.g., name, email address, photo) (i) among actual research data, (ii) only in a separate file for contact information, or (iii) not at all
  • Key actions
  • Key implications to other stages
    • In Stage 4: Update/align your data management plan with the data processing description
    • In Stage 5: Align the informed consent message to research participants with the data processing description, in case your study involves (a) or (b) above.
    • In Stage 6: Erase unnecessary direct identifier information gathered immediately, in case your study involves (a) or (b) and (i) or (ii) – or store it in a separate file , which is not associated with the actual research data file.
    • In Stage 10: Erase latest here unnecessary direct identifier information, in case you plan to archive and share the data through a long-term depository.
    • In stage 6, 9, and 10: Comply in your actual data collection and processing, with the data processing practices you indicate in the data processing description.

Stage 3 Fill in request for  ethical review. See Ethical review.

  • Must-do for whom?
    • Principal Investigator PI of the research team
    • Researchers of the research team
    • Doctoral students
    • BSc/MSc/eMBA students
  • Must-do when?
    • < 10% of studies, in case your study is one of the six types:
  1. a study in which you won’t be asking for Informed Consent from research participants (i.e., a study in which you won’t inform the participants beforehand, about the fact that they are being studied, or ask for their permission)
  2. a study in which you give research participants something to eat, drink, smell, or touch, as an intervention – or otherwise intervene their physical integrity
  3. a study in which you will expose participants to exceptionally strong stimuli (e.g., shocking pictures)
  4. a study in which the subjects are children under the age of 15, or represent other vulnerable groups/populations (e.g., asylum seekers)
  5. a study which might risk causing long-term mental harm to participants (e.g., trauma, depression, sleeplessness)beyond risks encountered in normal life
  6. a study which might risk causing physical harm or signify a security risk to subjects (e.g., studies concerning domestic violence)
  • Key decisions
    • Whether it is possible to redesign the study still, such that (1) informed consent can be asked, and/or the study will not involve aspects (2)-(6)
  • Key actions
    • Consider and plan to take all feasible measures to reduce the risk/probability that research participants are exposed to mental or physical harm, and the level of that harm
    • Fill in the ethical review request e-form in case your study represents one of the six types (1)-(6) above
    • Wait for 2 weeks for Hanken’s Research Ethics Committee to send you a reply about approving your research plan
  • Key implications to other stages
    • In Stage 4: Update/align your data management plan with ethical review request
    • In Stage 5: Align the informed consent message to research participants with the ethical review request

Stage 4 Write/update a data management plan (DMP). See Data managemnt plan (DMP).

  • Must-do for whom?
    • Principal Investigator PI of the research team
    • Researchers of the research team
    • (Usually not doctoral students)
    • (Usually not BSc/MSc/eMBA students)
  • Must-do when?
    • <30% of studies; To meet funder and other policy requirements, to promote open science, and to follow good research practices, write and update continuously a data management plan (DMP).
  • Key decisions
    • Whether to concentrate more on the technical management and protection of the database, or more on the personal data/privacy protection (especially if the DMP has a page limitation, much details on both can often not be fitted in)
  • Key actions
    • Write/update your DMP, in alignment with the data processing description (and potential ethical review request). You can use the DMP tool DMPTuuli or DMP templates to help you write a DMP. See DMP guides and checklists.
    • Indicate in the DMP in case you plan to target a journal that allows/requires submitting the dataset, or in case you plan to archive and share the data in a long-term depository.
  • Key implications to other stages
    • In Stage 10: Archive and share the data in a long-term depository, in case you plan to do so.

 

(2) DURING DATA COLLECTION (ACTIVE STATE OF RESEARCH)

Stage 5. Ask for informed consent from research participants. See Data collection.

  • Must-do for whom?
    • Principal Investigator PI of the research team
    • Researchers of the research team
    • Doctoral students
    • BSc/MSc/eMBA students – but usually not asking for informed consent, only informing the research participants briefly about non-personal data collection
  • Must-do for when?
    • <50% of studies; in case the data includes (a) personal data about individuals (e.g., consumers, customers, or investors) or (b) data gathered from individuals (e.g., company managers), that you yourself gather. (In case you utilize secondary data gathered by someone else, or some organization, you don’t have to ask for informed consent.)
  • Key decisions
    • Whether to ask the informed content with (a) signature on paper in the research situation, (b) checkbox on a survey questionnaire, (c) at the same time as agreeing an interview with a participant through email.
  • Key actions
    • Modify the consent message template to suit your study and align the information with the data processing description (filled in on stage 2)
    • Let the research participant know about the data processing in your study by showing your modified informed consent text to the participant at some point before collecting the data from him/her (e.g.,(a) signature on paper in the research situation, (b) checkbox on the first page of a survey questionnaire, OR (c) at the bottom of an email, when agreeing about an interview time and place with a participant)
  • Key implications to other stages
    • In stage 6, 9, and 10: Comply in your actual data collection and processing, with the data processing practices you indicate on the informed consent message.

Stage 6. Store, share, and back up data securely during research. See Data storage and backup.

  • Must-do for whom?
    • Principal Investigator PI of the research team
    • Researchers of the research team
    • Doctoral students
    • BSc/MSc/eMBA students
  • Must-do for when?
    • Always; 100% of studies
  • Key decisions
    • Whom to grant access to the data and to which data, and what access rights to be granted and why granted during the active research period
    • Whether to use other data storage and sharing services than those maintained by Hanken – in which case you need a Data Protection Agreement with the other service provider
  • Key actions
    • In the default case, use data storage services provided and maintained by Hanken[QX3] , including the researchers' own account on the Hanken network drive like H:\, Microsoft Office365 applications (e.g., Onedrive for Business),  Webropol, or SPSS.
    • Do not send the data per email to either other Hanken researchers or external researchers. Do not use other cloud-based services (eg., Dropbox, Google Docs, Onedrive for consumers) than Onedrive for Business. Do not use other survey platforms than Webropol.
    • If there is a pressing need to use other than Hanken-maintained services (Onedrive for Business, Webropol, SPSS, Office 365), you have to have a Data Processing Agreement with the service provider. Ask for more information from Hanken's Data Protection Officer dpo@hanken.fi.

 

(3) AFTER DATA COLLECTION (SHARING RESULTS)

Stage 7. Reconsider open access options before targeting and writing an article

Stage 8. Write a research article

Stage 9. Register your research in Haris. See Haris - Hanken's research database in LibGuides.

  • Must-do for whom?
    • Principal Investigator PI of the research team
    • Researchers of the research team
    • Doctoral students
    • (Usually not BSc/MSc/eMBA students)
  • Must-do for when?
    • Always; 100% of studies
  • Key decision
    • All Hanken researchers shall register your research merits in Haris: Register your publications (all), activities and projects, and update your profile in Haris.
    • To improve the visibility and impact of your research.
  • Key actions
    • Register your publication in Haris here. Remember to upload the post-print version or the publisher’s final PDF to Hairs (see Which version of the article can I self-archive? in LibGuides on open access).
    • Consider registering your dataset in Haris here. Remember to add a link to the repository where you have stored or published the data.

Stage 10. Choose suitable repositories to open and publish your data. See Data sharing and preservation.

  • In line with open science principles and practices, research data and related published research results produced at Hanken ought to be open and available for shared use.
  • Data with personal information can only be published anonymised. Pseudonymised data is still personal data, and therefore cannot be opened without explicit consent. See Anonymisation and Personal Data by the Finnish Social Science Data Archive (FSD).
  • Note that metadata of the data holding personal information can still be able to be opened.
  • Choose repositories which use persistent identifiers (DOI, URN).
  • Check re3data.org to find the right repository. General repository include Aila, IDA, Zenodo, Dryad, and Figshare.
  • Which license will you use to open and share your data? Agreements on data ownership and other intellectual property rights must be concluded before commencing any actual research activities. See Copyright and Agreements by the Finnish Social Science Data Archive (FSD) and Open Data by Creative Commons (CC).
  • If your data has long-term value, consider archiving your data in Fairdata-PAS by the Finnish Ministry of Education and Culture.