General questions

Your H index is the largest number X such that you have at least X publications with at least X citations. The H index is not directly available from the KI Bibliometric Verification Toolkit.

If you have no publications from before 1995 and have verified all your publications, you can still calculate H index from your list of verified publications in the bibliometric system.

Login and verify all your publications. (https://bibliometrics.ki.se/users/login)
Export them to Excel (or anything else that can read csv files) from the publication list in the Bibliometric Analysis Toolkit.
Sort the publications after times cited (with the most cited publications first and so on) and look in the sorted list where the number of citations is at least equal to the order number.

Example:

Order Citations
1 ......... 23
2 ......... 11
3 ......... 5
4 ......... 2
5 ......... 1

In this case, H index is 3, since publication number 3 has 5 citations (at least 3) but publication number 4 has 2 citations (less than 4).

If this seems cumbersome, or if you have publications older than 1995, you can instead get H index from Web of Science by searching all your publications and from the resulting list of publications select "Create Citation Report" (to the right above the search result to the right).

There are presently two ways that we can identify the research fields of individual articles. One is to use the Thomson Reuters journal subject field as a proxy for article content. This is very often used in bibliometric studies. But in medicine, many of the publications also have MeSH-terms, the controlled vocabulary from Medline, which are much more specific, and at Karolinska Institutet we often use these.

For publications in the intersection between the Web of Science and Medline, both citation data and detailed subject information at an article level are available. At Karolinska Institutet we often use this type of intersection to single out publications in Medicine and Life Science from all Web of Science records from other research institutions. This makes it possible to do better comparative analyses between us, as a medical university, and research institutions with more than one faculty.

By logging in to the KI Bibliometric Verification Toolkit you accept that we retrieve information (including your civic registration number) from the KI/SLL staff databases for computerized use in the Karolinska Institutet bibliometric system in accordance with the Swedish law on handling of personal data (PUL, SFS 1998:204).

This will enable us to match staff records between the Karolinska Institutet staff database (KIMKAT) and the SLL staff database (EK) and create a single KI/SLL bibliometric verification account for each user. We will not share information retrieved from the staff databases with anyone outside the KI/SLL organization. If you have any additional questions about our use of the information in KIMKAT/EK, please contact us at bibliometrics@ki.se.

If you decline this request, please contact us at bibliometrics@ki.se and inform us on how you wish your account to be handled. If you wish to have a joint KI/SLL account in the Karolinska Institutet bibliometric database, you must include both your KI-login and your HSA-id in your e-mail. If you choose not to inform us, this may result in your verified publications not being included in bibliometric analyses results.

The information we retrieve from KIMKAT/EK is:

• Login
• Unique database identifier
• First name
• Last name
• Civic registration number (Personnummer)
• E-mail address
• Organizational affiliation to department, hospital, division and clinic (where applicable)
• Affiliation Type and Role (eg. Employee, Graduate student, Research Assistant)

Owner of the Karolinska Institutet bibliometric database is the research board of Karolinska Institutet. The Karolinska Institutet University Library (Berzelius väg 7B, Solna) is responsible for developing and running the bibliometric database. Non-licensed information in the bibliometric database is subject to the principle of public access to official documents and that information is available to the general public on request. You are entitled to a print out of the information about you that is stored in the Karolinska Institutet bibliometric system (free of charge). To receive this, send a signed, written request to Karolinska Institutet University Library, Att: Malin Cantwell, Fe 200, 171 77 Stockholm.

The Karolinska Institutet University Library will, upon request by the registered person or if an error is found by the University Library in the personal data processed take steps to correct, block, restrict or erase as soon as practicable such personal data as has not been processed in accordance with the Personal Data Act or regulations issued under the Act. (For example, this may relate to incorrect data.) You may report any errors to bibliometrics@ki.se or to Karolinska Institutet University Library, Att: Malin Cantwell, Fe 200, 171 77 Stockholm who will put you in contact with the person/persons responsible for the primary data source of the incorrect data.

Read more about PUL at the data inspection. 

The system is optimized for Internet Explorer 7, Internet Explorer 8 and Mozilla Firefox. The system uses JavaScript.

An orange griffin is sometimes displayed when a user in one of the university hospitals is logged in on the KI library web site or proxy server and then tries to log in to the bibliometric verification toolkit as well.

Please close all web browser windows and then go directly to the login page of the bibliometric verification toolkit (http://bibliometrics.ki.se/users/login) without passing another KI login service.

Bibliometric indicators are calculated for each publication individually. Indicators for an individual researcher will be shown when this person logs in to the Karolinska Institutet bibliometric database. An analysis based on field normalized indicators for an individual researcher with less than 50 publications cannot be ordered by someone else.

List of indicators available through the bibliometric system (For a full list of bibliometric indicators and explanations to how they are calculated, see “Bibliometric handbook for Karolinska Institutet” and “Bibliometric indicators - definitions and usage at KI”).

• P: Number of publications identified with the current analyzed set of publications.
• At KI/SLL: Number of verified publications with a recognizable KI address (including university hospitals). Verified means that the publications in the Karolinska Institutet bibliometric database have both been identified by the researcher in question and that an organizational affiliation has been supplied by him/herself.
• C: Total number of citations
  The Total number of citations is the sum of citations (self citations included) from all publications present in the database to all verified publications for the analyzed set of publications.
• c: Number of citations to a single publication
• c_f:: Field Normalized Citation Score for a single publication
  The Item Oriented Field Normalized Citation Score normalizes the number of citations to a single verified publication by comparing it to the mean number of citations to documents of the same type, published the same year, in the same research area.
• Avg C_f: Field Normalized Citation Score Average
  The average Field Normalized Citation Score is calculated on The Item Oriented Field Normalized Citation Score for all verified publications for the current analyzed set of publications. The world average is about 1, and an indicator of for example 1.2 means that the analyzed group of articles is cited 20% above the world average. (At present the standard method of using the ISI Journal Classifications to identify the research area is being used.)
• Sum C_f: Total Field Normalized Citation Score
  The sum of all the item oriented field normalized citation scores for all verified publications for the active selection.
• P_f5%: Field Normalized Top Publications
  The indicator Field Normalized Top Publications shows the number of verified publications for the active selection that belong to the 5% most cited publications in the world. The normalization is made by comparing the number of citations to each verified publication to the 95th percentile of citation distruibution to all publications from the same year, in the same subject and of the same document type. (At present the standard method of using the ISI Journal Classifications to identify the research area is being used).
• Share P_f5%: Field Normalized Share of Top Publications
  The indicator Field Normalized Share of Top Publications shows the percentage of verified publications for the current analyzed set of publications that belong to the 5% most cited publications in the world. The normalization is made by comparing the number of citations to each verified publication to the 95th percentile of the average citations to all publications from the same year, in the same subject and of the same document type. (At present the standard method of using the ISI Journal Classifications to identify the research area is being used).
• JIF: ISI Journal Impact Factor
  The ISI Journal Impact Factor is a measure of the frequency with which the "average article" in a journal has been cited in a particular year. The ISI impact factor for a specific journal, one specific year (Y), is calculated by counting the number of citations to articles in that journal the two preceding years (Y-1 and Y-2) from publications in year Y and dividing this with the number of publications.
• ∑ JIF: Sum of ISI Journal Impact Factors
  The sum of the ISI Journal Impact Factors connected to each verified article or review in the active selection.
• Avg JIF: Average of ISI Journal Impact Factors
  The average of the ISI Journal Impact Factors connected to each verified article or review in the active selection.

Note!

No field normalized indicators are calculated for

• too recent publications (with a publication year equal to the present year or last year)
• publications belonging to fields with fewer than 30 publications per year
• publications belonging to fields with an average citation rate lower than 0,2 cites per year
• for a subset of publications less than 50 publications

Moreover, the compiled indicators are only based on publications with document type "Article" or "Review".

This is to ensure statistical stability.

In the verification toolkit each verified publication with a not too recent publication year (see note above) also displays the value of the Item Oriented Field Normalized Citation Score for that individual publication, and will if it is one of the 5% most highly cited publications from that year in its field show a text indicating this.

For a copublication analysis we use information about who wrote the article and where they were active when they wrote it as a proxy for the research institution or country involved.

However, the quality of this data in the Web of Science is limited. Different people may publish under the same name, and some researchers (especially those with a double family name) may be published under many different name forms. Also the quality of addresses may bee of varying level with dozens of different versions of for example Karolinska Institutiet.

Using the information in the addresses field, we can for instance look at co-publication at the country level. This kind of list is useful when assessing the level of international collaboration.

We can also look at the different authors in the publications and list the most frequent co-authors. Combining author and address information, we can also see who at Karolinska Institutet publish together with which organizations in one specific country or within any other subset of publications we can define, such as a subject field or a specific set of journals.

Using the information in the addresses field, we can look at co-publication at the organizational level, for example all KI publications together with Chinese organizations. This kind of analysis is useful for finding potential organizations for a formalized cooperation, or to evaluate already active cooperation agreements.

Within Karolinska Institutet we can use the higher data quality ensured by the verification process where we get to know the different namestrings to an individual researcher and the standardized affiliation of every publication in order to do copublication analysis with much more detail than otherwise possible.

There are presently two ways that we can identify the research fields of individual articles. One is to use the Thomson Reuters journal subject field as a proxy for article content. This is very often used in bibliometric studies. But in medicine, many of the publications also have MeSH-terms, the controlled vocabulary from Medline, which are much more specific, and at Karolinska Institutet we often use these.

An analysis of the journal categories of a unit’s/persons publications gives an indication of in which areas the analyzed unit is active. From this type of analysis, it is also possible to identify the type of audience that can be expected to read, and potentially cite the publications. It can be used as the basis for a discussion about whether this is where you want to publish and be seen.

An analysis of the MeSH-terms is much more specific and can help you see how your publications are shown in an international database like Medline, ie what other researchers need to search for in order to find your publications. If you don’t know the analyzed group, you can see what major and peripheral aspects of research the group is involved in for instance for your Institution/clinic.

Combined with information about individual authors and/or organizations we can produce maps that show what factions co-publish in which certain areas.

At present, the bibliometric database is directly based on the Web of Science databases produced by Thomson Reuters and Medline. The system is limited to records available in those databases from 1995 and forward. Articles indexed by PubMed or any other database are at the moment available only if they are also included in the Web of Science databases or Medline.

The Web of Science web interface also includes proceedings papers. These are not available in the Karolinska Institutet bibliometric system.

The primary aim of the Karolinska Institutet/SLL bibliometric database is to furnish Karolinska Institutet/SLL managers, departments/clinics and employees with high quality bibliometric analyses and reports (regarding e.g. publication patterns, co-publication partners and/or by-subject breakdowns). The results provide overviews of the research being conducted by KI/SLL researchers as well as tools that enable scientific results to be compared internally and with the work being done in other countries. Analyses results can also be used to follow up and plan activities, and sometimes even to assess and reward scientific quality.

The incentives from the board of research for publishing could be condensed to:

• Before you publish, do a little background research into the journal to which you intend to submit your article; it should be included in the Web of Science index.
• Check the journal’s impact factor and consider whether you can choose one with a higher value.
• One high-cited article usually gives better returns on the bibliometric indicators than several low-cited articles.
• Verify all your publications. It is essential to the quality of the database, and there is an explicit intention for the choice of bibliometric model to be such that the verification of all your publications has an aggregate positive effect.

Read the full recommendations (PDF).
 

Recommendations

the use of bibliometric
indicators at an individual level

Within Karolinska Institutet and the Stockholm County council (SLL) there are recommendations for if and how bibliometric methods should be used with data for individual researchers.

Bibliometric methods are less suitable for the assessment of individuals or smaller groups. It is unusual for these to achieve a publication quantity sufficient for the results to be reliable and stable. It is also important that analyses methods do not create undesirable incentives for publication and verification behaviour, and one expressed intention with bibliometric analyses within KI/SLL is that verification of a publication should never be counterproductive for an individual researcher. With good knowledge of the limitations existing at the level of the individual, certain bibliometric measures can also be used to supplement visual inspection of a publication list.

Read the full recommendations concering the use of bibliometric indicators at an individual level.

It is possible, and desirable, for authors to verify all of their publications, also when written at other organizations than Karolinska Institutet/SLL. This is because two different types of analyses may be of value in different situations.

The internationally more common type of analysis, the “organization-based” analysis, uses knowledge about where the publications were written. It mirrors everything done by an organization during a certain time. This is the method of choice if one wishes to study the development over time of a specific research environment such as a university.

An organization based analysis of one individual Karolinska Institutet author will include the publications that he/she wrote while active at Karolinska Institutet. At Karolinska Institutet/SLL data for this type of analysis comes either from the authors' addresses as written on the publications or from the addresses that the authors supplied when they verified the publication in the bibliometric system.

An “author-based” analysis includes all publications written by researchers presently affiliated to the analyzed organization, regardless of where they were active when they wrote it. This more accurately mirrors the current research potential of the organization and is therefore the method used for many bibliometric analyses within Karolinska Institutet.

At Karolinska Institutet/SLL data for this type of analysis comes from the authors' current affiliations according to the staff catalogues KIMKAT and EK."

You can search for a journal's impact factor in the database Journal Citation Reports (JCR)

You can log in with either a KI-login (KI) or a HSA-id (SLL). Choose which option you want to use by clicking the either the KI Login button or the SLL Login button on the login page.

KI-login: The Karolinska Institutet IT Centrum offers e-mail accounts, KI-login and VPN (Virtual Private Network) http://intra.ki.se/it/kiid/index_en.html.

HSA-id: SLL uses a login name of 4 characters called HSA-id for most SLL-systems. To be able to login to the bibliometric system you also have to use one of two authentication options

• a card reader connected to your computer
• a temporary authentication code via SMS (If you do not have your mobile phone number registered in EK you will have to contact your local EK-administrator and get your number registered first)

It's safe to click Yes here. If you click No the export to Excel will not open.

Information about the use of bibliometrics in the allocation of research funds from KI/SLL to departments/clinics is available at Bibliometrics at Karolinska Institutet and Stockholm County Council